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NASA NTRS2002

Theoretical Studies of Microphysics of Marine Boundary-Layer Clouds

This project is aimed at better understanding the role that aerosols play in altering the properties of stratus clouds. This interaction, termed the indirect effect of aerosols on climate, is a major subject a of study since the radiative forcing involved may rival that of greenhouse gases, but may be of the opposite sign. Our goal was to create numerical models of the phenomena, test them with data, and thereby gain insight into the physical processes occurring. Below we list the papers that we have produced during this grant. We then discuss these papers.

Toon, Owen B.↗
NASA NTRS2023

The Coupling Between Tropical Meteorology, Aerosol Lifecycle, Convection, and Radiation, During the Clouds, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex)

The NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex) employed the NASA P-3, Stratton Park Engineering Company (SPEC) Learjet 35, and a host of satellites and surface sensors to characterize the coupling of aerosol processes, cloud physics, and atmospheric radiation within the Maritime Continent’s complex southwest monsoonal environment. Conducted in the late summer of 2019 from Luzon Philippines in conjunction with the Office of Naval Research Propagation of Intraseasonal Tropical OscillatioNs (PISTON) experiment with its R/VSally Ride stationed in the North Western Tropical Pacific, CAMP2Ex documented diverse biomass burning, industrial and natural aerosol populations and their interactions with small to congestus convection. The 2019 season exhibited El Nino and associated drought, high biomass burning emissions, and an early monsoon transition allowing for observation of pristine to massively polluted environments as they advected through intricate diurnal mesoscale and radiative environments into the monsoonal trough. CAMP2Ex’s preliminary results indicate 1) increasing aerosol loadings tend to invigorate congestus convection in height and increase liquid water paths; 2) lidar, polarimetry, and geostationary Advanced Himawari Imager remote sensing sensors have skill in quantifying diverse aerosol and cloud properties and their interaction; and 3) high resolution remote sensing technologies are able to greatly improve our ability to evaluate the radiation budget in complex cloud systems. Through the development of innovative informatics technologies, CAMP2Ex provides a benchmark dataset of an environment of extremes for the study of aerosol, cloud and radiation processes as well as a crucible for the design of future observing systems.

CAMP2Ex↗
DOE OSTI2026

Weak, shallow, dry convection over Angola increases offshore stratocumulus cloud droplet number concentrations

Boundary-layer cloud interactions involving shortwave-absorbing aerosols remain one of the least understood aerosol influences on climate. Here, we find the highest stratocumulus cloud droplet number concentrations over the southeast Atlantic occur when agricultural fires coincide with synoptically-weakened surface warming over Angola, occurring June-early August. Dry convection fills a shallow continental boundary layer with smoke, and a nighttime (local solar time 2-9) land breeze transports the aerosol into the marine boundary layer. Offshore aerosol transport is strengthened by low-level easterlies from a continental pressure high southeast of Angola. Simultaneously, the South Atlantic subtropical high is weaker, allowing extensive dispersal of aerosol offshore into the boundary layer, obscuring cloud brightening from shipping. Meteorological co-variation at synoptic scales compensates for cloud brightening by the smoke. Outgoing shortwave radiation increases by 15–20% of the monthly mean in June and July when offshore droplet numbers are less but the stratocumulus deck is more developed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Assessing the Effects of Anthropogenic Aerosols on Pacific Storm Track Using a Multiscale Global Climate Model

Atmospheric aerosols impact weather and global general circulation by modifying cloud and precipitation processes, but the magnitude of cloud adjustment by aerosols remains poorly quantified and represents the largest uncertainty in estimated forcing of climate change. Here we assess the impacts of anthropogenic aerosols on the Pacific storm track using a multi-scale global aerosol-climate model (GCM). Simulations of two aerosol scenarios corresponding to the present day and pre-industrial conditions reveal long-range transport of anthropogenic aerosols across the north Pacific and large resulting changes in the aerosol optical depth, cloud droplet number concentration, and cloud and ice water paths. Shortwave and longwave cloud radiative forcing at the top of atmosphere are changed by - 2.5 and + 1.3 W m-2, respectively, by emission changes from pre-industrial to present day, and an increased cloud-top height indicates invigorated mid-latitude cyclones. The overall increased precipitation and poleward heat transport reflect intensification of the Pacific storm track by anthropogenic aerosols. Hence, this work provides for the first time a global perspective of the impacts of Asian pollution outflows from GCMs. Furthermore, our results suggest that the multi-scale modeling framework is essential in producing the aerosol invigoration effect of deep convective clouds on the global scale.

aerosol-cloud-climate interaction↗
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↗
DOE OSTI2018

Development and Rigorous Validation of Modules for Predicting Organic Aerosol CCN Activity from Molecular Properties

The indirect interaction of anthropogenic aerosols with clouds (aerosol indirect forcing) represents one of the main uncertainties in climate projections, and reducing this uncertainty requires improved understanding of the aerosol life cycle, including atmospheric aging and the ability to nucleate cloud droplets or crystals. A key parameter that links the chemical properties of aerosol to its nucleating properties, and ultimately to aerosol indirect forcing, is its hygroscopicity (ability to uptake water). One way to compare and systematize the ability of various chemical compounds or particle types to nucleate cloud drops is via the hygroscopicity parameter κ, which can be used directly in global models to simulate aerosol indirect forcing. In this project we further investigated the relationships between the chemical composition of organic aerosol particles, which are known to be important components of atmospheric particulate matter, and their ability to serve as cloud condensation nuclei (CCN). In particular, we isolated the role of viscosity on κ by applying methods similar to those we used previously in our DOE/ASR research. Our motivation for the focus on viscosity was through its link to particle phase state. Particle phase affects water uptake on timescales relevant to the laboratory and also likely relevant to atmospheric processes, with reduced apparent hygroscopicities for semisolid and solid particles, compared with liquid particles. Water uptake itself affects viscosity, an important feedback that we explored in this project. The objectives of the project were as follows: (1) measure the effects of molecular structure, temperature, and relative humidity on the viscosity of organic aerosol formed via controlled laboratory experiments, (2) measure the effects of organic aerosol viscosity on water uptake and CCN activity above and below water saturation, (3) further develop the κ parameterization of organic aerosol hygroscopicity to include viscosity/phase, and (4) experimentally validate the κ parameterization for organic aerosol with chemical composition ranging from relatively simple to complex. It was proposed that particle viscosity exerts a kinetic control on equilibrium water uptake. High viscosity was expected to delay water uptake based on diffusional limitations. This would manifest itself in reduced observed CCN activity or κ. Understanding the interplay between water content and viscosity (composition control on particle viscosity) and between viscosity and equilibrium water content (diffusional control on water uptake) were the overall science objectives of this grant. Targeted experiments were carried out to test the kinetic control hypothesis. These experiments included studies that explicitly measured the equilibration time scale of water uptake, and experiments that tested the role of viscous particle coatings on the observed CCN activity. From the combined work, it is concluded that mass transfer limitations by glassy organic particles are unlikely to affect cloud droplet activation near laboratory temperatures. This implies that viscosity does not need to be included in parameterizations that link particle chemical composition and κ. A parameterization to predict κ through the UNIFAC group contribution method was developed with previous ASR funding. As planned, this computational module was further developed and validated here through targeted laboratory studies. The computational module has been made available as free software under the GNU public license. A database of κ-values to aid model development has been compiled and is available online via an open access model. In conducting this work, significant effort was made to understand how aerosol composition, including the associated aerosol water content, affects viscosity. This included a study detailing the influence of functional group composition on organic aerosol viscosity. We identified a strong link between volatility and viscosity. Functional groups responsible for low vapor pressure also promote high viscosity. Specifically, carboxylic acid and hydroxyl groups were identified as major contributors to high viscosity. Several studies were carried out to characterize the link between composition and the glass-to-liquid phase transition. Compositions tested include models of organic/inorganic particles and models of complex organic aerosol formed through secondary processes. A simple computational model to predict the amorphous phase diagram was developed and tested. Excellent agreement between model and measurements was obtained for organic/inorganic mixtures. The computational model is simple enough to be included in global model simulations. However, constraints of input parameters such as the Gordon-Taylor constant for binary mixtures for a wide range of complex mixtures have not yet been fully evaluated. Combined, the performed work provides new constraints on the amorphous phase state of organic aerosols.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Aircraft Video Camera (CAM-AIR) Instrument Handbook

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Aerial Facility (AAF) video cameras are installed in the cockpit of ARM’s research aircraft looking forward and in the belly of the plane looking down at the ground. Prior to the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign in the Azores during 2017, the P1344 camera was flown in the forward (cockpit) position and the P1347 camera was flown in the nadir (belly) position. Since only the forward camera was flown for ACE-ENA and the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina during 2018–2019, the camera with the higher resolution (P1347) was moved to the cockpit.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Evaluating and Improving Convective Parameterization for GCMs Using ARM Observations. Final report

This technical report summarizes the achievements during the project period funded by the Atmospheric System Research (ASR) program. The general goal of the project is to improve the representation of atmospheric deep convection in global climate models. By using DOE Atmospheric Radiation Measurement (ARM) program observations and a hierarchy of models from cloud-resolving to global climate models, we evaluated and improved many aspects of convection parameterization schemes, such as the trigger function for convection and closure condition to determine the amount of convection. We also incorporated the stochasticity of convection into a convection scheme. These improvements, when implemented into the National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM) and the DOE Exascale Energy Earth System Model (E3SM), led to improved simulation of precipitation characteristics, including precipitation intensity, Intertropical Convergence Zone, and Madden-Julian oscillation. The project also improved the representation of microphysical processes in convective clouds. It enables the interaction of cloud microphysics with aerosols in weather and climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Department of Energy’s Atmospheric System Research (ASR) Program’s Workshop on the Future of Atmospheric Large Eddy Simulation (LES) (Workshop Report)

Large-eddy simulation (LES) is used as a tool to understand physical processes such as turbulence, aerosols, clouds, precipitation, radiation, the interactions among all these, and their interactions with the underlying surface. Over the next 10 years, LES will drive fundamental progress in open scientific questions in these areas as LES is increasingly used to gain understanding of complex interacting physical processes involving atmospheric turbulence. This growth will be driven both by scientific demand and the expansion of computational resources needed to conduct LES, and the form that the growth takes will largely be determined by how computational resources are leveraged for scientific gain. In particular, we suggest that computational resources are likely to be leveraged in two separate but not necessarily distinct ways. On one hand, growth in computational resources will allow LES to be made more routine, that is, performed more frequently, while on the other hand, the computational expense (measured in total floating point operations) afforded to individual LES will expand dramatically, allowing simulations to increase in both domain size and resolution as well as physical detail.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

MOSAiC Radar b1 Processing: Corrections, Calibrations, and Processing Report

The U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) user facility deployed many instruments on board a German ice breaker, the Research Vessel (RV) Polarstern, for one year from October 2019 to October 2020. The purpose of the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) field campaign was to study the decline in the sea-ice pack around the North Pole, and what factors may be at play. After the campaign ended, efforts were undertaken to provide a calibrated radar data set for future studies. MOSAiC presented new challenges to this process, as existing methodologies often were not applicable for the frozen environment with little to no ground clutter, and concurrent engineering updates or calibrations could not be accomplished once the ship set off. Like the previous Cloud, Aerosol, and Complex Terrain Interactions (CACTI) and Cold-air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) documentation (Hardin et al. 2020, Matthews et al. 2023), the data correction and calibration process is known in ARM as creating a “b1” datastream. This means that the radar datastreams have been well characterized to the best possible quality. This report will detail the status of the raw “a1” level data sets during the MOSAiC campaign, the corrections that were applied to create the “b1” data files, and the details of the applied methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Fixed-Site KAZR b1 Data Processing: Corrections, Calibrations, and Processing Report

The U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) User Facility operates three fixed-site observatories: Eastern North Atlantic (ENA), North Slope of Alaska (NSA), and Southern Great Plains (SGP). Each fixed site has a wide variety of atmospheric instrumentation that has been collecting data for at least 10 years (NSA and SGP over 25 years). Each site is unique because it represents a different climate state. The environment at ENA is characterized by marine stratocumulus clouds and one of the key scientific areas of focus is the interaction of these clouds with aerosols. At NSA the focus is on arctic climate and cloud and radiative processes in a high-latitude environment. SGP represents a mid-latitude, mid-continent climate that experiences environmental cycles on diurnal and seasonal time scales. The ARM observatories are all meant to improve understanding of atmospheric processes that can then be better incorporated into weather and climate models. Another common thread between the fixed sites is the focus on cloud processes. Each site is equipped with at least one radar that provides continuous remote-sensing observations of clouds and precipitation. This report details the analysis of a1-level radar data at the fixed sites and the process for generating b1-level data. While b1-level data have been produced for ARM campaigns at the mobile facilities, this is the first analysis led by ARM radar mentors to correct data at the fixed sites. In particular, we focus on calibrations and corrections of the Ka-band ARM Zenith Radars (KAZRs) at ENA, NSA, and SGP. Ongoing and future work will involve corrections applied to other fixed-site radars.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Collaborative Proposal: Improving understanding of the internal structure and dynamics of deep convection using ARM observations and large eddy simulations

Recent observational and large eddy simulation (LES) modeling studies have nearly unanimously supported the view of deep cumulus convection being composed of a series of quasi-spherical bubbles of buoyant air, known as moist thermals. Despite the prevalence of moist thermals in deep convection, a comprehensive theory for the dynamics of these structures is lacking. Most current conceptual models for cumulus convection are based on canonical scaling theories for dry thermals or plumes; however, there is considerable evidence that the behavior of moist thermals differs markedly from these theories. Furthermore, the theoretical basis for most cumulus parameterizations originates from the plume conceptual model, and therefore these parameterizations are inconsistent with the real structure of moist convection. Motivated by the aforementioned knowledge gaps, this “end-to-end” research effort use theory, observations, numerical simulations, and direct improvements to the Zhang-McFarlane (ZM) convection scheme in the global climate Community Atmosphere Model (CAM) to address the following research questions: What key environmental parameters determine whether or not shallow convection will transition into deep convection, in the context of thermal-like updrafts? What factors regulate the size of thermals within cumulus updrafts? How does vertical wind shear influence thermal behavior, and as a consequence, vertical velocity and mass flux profiles and the shallow-to-deep convective transition? What are the critical processes that determine updraft vertical velocities and their connection to the vertical mass flux profile for thermal-like updrafts? Idealized LES modeling will be used in conjunction with theoretical models for the core properties of thermal-like updrafts to better understand key processes that regulate thermal ascent rates and entrainment properties. Thermal-tracking procedures will be used to characterize the behavior of thermals within the LES, and recently developed direct measures of entrainment and detrainment will be used to quantify entrainment/detrainment rates. Building from these results, we will analyze the structure of moist thermals from hemispheric range-height indicator scans taken during the Atmospheric Radiation Measurement Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign, and from “real case” LES of CACTI events. This combined modeling and observational analysis will provide essential validation for the existing body of research on moist thermal dynamics, which is based primarily on modeling studies. With the insight gained from the aforementioned activities, we will modify the Zhang-McFarlane convection scheme to improve its representation of updraft vertical velocity and entrainment rate profiles. These process-level changes will be tested in the Community Atmosphere Model to assess the impact on global climate simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

CACTI Radar b1 Processing: Corrections, Calibrations, and Processing Report

The U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) user facility deployed a large number of instruments to a region nearby the Sierra de Córdobas mountains in Argentina as part of the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign (1). During this campaign, four radars were installed at a site outside of Villa Yacanto as shown in Figure 1. As part of a post-campaign effort to improve the usability of these data, a significant activity was undertaken towards the calibration, correction, and improvement of the data quality of these radar datastreams. This process in ARM nomenclature is referred to as generating a “b1” datastream. While these “b1” standards may imply different corrections or standards for various ARM instruments, for radars it refers to a datastream that has been calibrated (and cross-calibrated), including a serious effort to deliver the highest-quality (well-characterized) data possible. This report details (i) the status/quality of the original “a1” (raw) data, (ii) the corrections and calibrations that are applied to generate these b1 datastreams, (iii) the details of the applied algorithms and how radar offset/calibration numbers were determined for the eventual corrections, and (iv) the new and flexible plug-in-based processing system designed during CACTI for radar b1 activities (current, future) that interfaces with ARM’s Data Integrator (ADI) and high-performance computing (HPC) system.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Drop Size Distribution Variability in Central Argentina during RELAMPAGO-CACTI

The Remote sensing of Electrification, Lightning, And Meso-scale/micro-scale Processes with Adaptive Ground Observations (RELAMPAGO) and the Cloud, Aerosol, and Complex Terrain Interactions Experiment Proposal (CACTI) field campaigns provided an unprecedented thirteen-disdrometer dataset in Central Argentina during the Intensive (IOP, 15 November to 15 December 2018) and Extended (EOP, 15 October 2018 to 30 April 2019) Observational Periods. The drop size distribution (DSD) parameters and their variability were analyzed across the region of interest, which was divided into three subregions characterized by the differing proximity to the Sierras de Córdoba (SDC), in order to assess the impact of complex terrain on the DSD parameters. A rigorous quality control of the data was first performed. The frequency distributions of DSD-derived parameters were analyzed, including the normalized intercept parameter (logN w ), the mean volume diameter (D 0 ), the mean mass diameter (D m ), the shape parameter (μ), the liquid water content (LWC), and the rain rate (R). The region closest to the SDC presented higher values of logN w , lower D 0 , and higher μ, while the opposite occurred in the farthest region, i.e., the concentration of small drops decreased while the concentration of bigger drops increased with the distance to the east of the SDC. Furthermore, the region closest to the SDC showed a bimodal distribution of D 0 : the lower values of D 0 were associated with higher values of logN w and were found more frequently during the afternoon, while the higher D 0 were associated with lower logN w and occurred more frequently during the night. The data were analyzed in comparison to the statistical analysis of Dolan et al. 2018 and sorted according to the classification proposed in the cited study. The logN w -D 0 and LWC-D 0 two-dimensional distributions allowed further discussion around the applicability of other mid-latitude and global precipitation classification schemes (startiform/convection) in the region of interest. Finally, three precipitation case studies were analyzed with supporting polarimetric radar data in order to relate the DSD characteristics to the precipitation type and the microphysical processes involved in each case.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Impact of aerosols on ice crystal size

The interactions between aerosols and ice clouds represent one of the largest uncertainties in global radiative forcing from pre-industrial time to the present. In particular, the impact of aerosols on ice crystal effective radius (R ei ), which is a key parameter determining ice clouds' net radiative effect, is highly uncertain due to limited and conflicting observational evidence. Here we investigate the effects of aerosols on R ei under different meteorological conditions using 9-yearsatellite observations. We find that the responses of R ei to aerosol loadings are modulated by water vapor amount in conjunction with several other meteorological parameters. While there is a significant negative correlation between Rei and aerosol loading in moist conditions, consistent with the “Twomey effect” for liquid clouds, a strong positive correlation between the two occurs in dry conditions. Simulations based on a cloud parcel model suggest that water vapor modulates the relative importance of different ice nucleation modes, leading to the opposite aerosol impacts between moist and dry conditions. When ice clouds are decomposed into those generated from deep convection and formed in situ, the water vapor modulation remains in effect for both ice cloud types, although the sensitivities of R ei to aerosols differ noticeably between them due to distinct formation mechanisms. The water vapor modulation can largely explain the difference in the responses of R ei to aerosol loadings in various seasons. A proper representation of the water vapor modulation is essential for an accurate estimate of aerosol–cloud radiative forcing produced by ice clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

The relative impact of cloud condensation nuclei and ice nucleating particle concentrations on phase partitioning in Arctic mixed-phase stratocumulus clouds

This study investigates the interactions between cloud dynamics and aerosols in idealized large-eddy simulations (LES) of Arctic mixed-phase stratocumulus clouds (AMPS) observed at Oliktok Point, Alaska, in April 2015. This case was chosen because it allows the cloud to form in response to radiative cooling starting from a cloud-free state, rather than requiring the cloud ice an dliquid to adjust to an initial cloudy state. Sensitivity studies are used to identify whether there are buffering feedbacks that limit the impact of aerosol perturbations. The results of this study indicate that perturbations in ice nucleating particles (INPs) dominate over cloud condensation nuclei(CCN) perturbations; i.e., an equivalent fractional decrease in CCN and INPs results in an increase in the cloud-top long wave cooling rate, even though the droplet effective radius increases and the cloud emissivity decreases.The dominant effect of ice in the simulated mixed-phase cloud is a thinning rather than a glaciation, causing the mixed-phase clouds to radiate as a grey body and the radiative properties of the cloud to be more sensitive to aerosol perturbations. It is demonstrated that allowing prognostic CCN and INPs causes a layering of the aerosols, with increased concentrations of CCN above cloud top and increased concentrations of INPs at the base of the cloud-driven mixed layer. This layering contributes to the maintenance of the cloud liquid, which drives the dynamics of the cloud system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Deep-learning-derived planetary boundary layer height from conventional meteorological measurements

Abstract. The planetary boundary layer (PBL) height (PBLH) is an important parameter for various meteorological and climate studies. This study presents a multi-structure deep neural network (DNN) model, which can estimate PBLH by integrating the morning temperature profiles and surface meteorological observations. The DNN model is developed by leveraging a rich dataset of PBLH derived from long-standing radiosonde records augmented with high-resolution micro-pulse lidar and Doppler lidar observations. We access the performance of the DNN with an ensemble of 10 members, each featuring distinct hidden-layer structures, which collectively yield a robust 27-year PBLH dataset over the southern Great Plains from 1994 to 2020. The influence of various meteorological factors on PBLH is rigorously analyzed through the importance test. Moreover, the DNN model's accuracy is evaluated against radiosonde observations and juxtaposed with conventional remote sensing methodologies, including Doppler lidar, ceilometer, Raman lidar, and micro-pulse lidar. The DNN model exhibits reliable performance across diverse conditions and demonstrates lower biases relative to remote sensing methods. In addition, the DNN model, originally trained over a plain region, demonstrates remarkable adaptability when applied to the heterogeneous terrains and climates encountered during the GoAmazon (Green Ocean Amazon; tropical rainforest) and CACTI (Cloud, Aerosol, and Complex Terrain Interactions; middle-latitude mountain) campaigns. These findings demonstrate the effectiveness of deep learning models in estimating PBLH, enhancing our understanding of boundary layer processes with implications for improving the representation of PBL in weather forecasting and climate modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

An extended radar relative calibration adjustment (eRCA) technique for higher-frequency radars and range–height indicator (RHI) scans

Abstract. This study extends the relative calibration adjustment technique for calibration of weather radars to higher-frequency radars as well as range–height indicator (RHI) scans. The calibration of weather radars represents one of the most dominant sources of error for their use in a variety of fields including quantitative precipitation estimation and model comparisons. While most weather radars are routinely calibrated, the frequency of calibration is often less than required, resulting in miscalibrated time periods. While full absolute calibration techniques often require the radar to be taken offline for a period of time, there have been online calibration techniques discussed in the literature. The relative calibration adjustment (RCA) technique uses the statistics of the ground clutter surrounding the radar as a monitoring source for the stability of calibration but has only been demonstrated to work at S- and C-band for plan-position indicator (PPI) scans at a constant elevation. In this work the RCA technique is modified to work with higher-frequency radars, including Ka-band cloud radars. At higher frequencies the properties of clutter can be much more variable. This work introduces an extended clutter selection procedure that incorporates the temporal stability of clutter and helps to improve the operational stability of RCA for relatively higher-frequency radars. The technique is also extended to utilize range–height scans from radars where the elevation is varied rather than the azimuth. These types of scans are often utilized with research radars to examine the vertical structure of clouds. The newly extended technique (eRCA) is applied to four Department of Energy Atmospheric Radiation Measurement (DOE ARM) weather radars ranging in frequency from C- to Ka-band. Cross comparisons of three co-located radars with frequencies C, X, and Ka at the ARM Cloud, Aerosol, and Complex Terrain Interactions (CACTI) site show that the technique can determine changes in calibration. Using an X-band radar at the ARM Eastern North Atlantic (ENA) site, we show how the technique can be modified to be more resilient to clutter fields that show increased variability, in this case due to sea clutter. The results show that this technique is promising for a posteriori data calibration and monitoring.

47 OTHER INSTRUMENTATION↗