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Newsom, Rob

Publications and source records attributed to Newsom, Rob.

At least 73 records · Page 4

Aerosol and Cloud Optical Properties from the ARM Raman Lidars: The Feature Detection and Extinction (RLPROF-FEX) Value-Added Product

Aerosols and their interactions and influence on clouds are among the main sources of uncertainties in radiative direct and indirect forcing (IPCC 2013). Continuous height-resolved measurements of cloud and aerosol optical properties are needed to reduce these uncertainties. Here we describe the Raman Lidar Profiles – Feature detection and Extinction (RLPROF-FEX) Value-Added Product (VAP) derived using Raman lidar data at multiple U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility sites. RLPROF-FEX provides estimates of extinction, backscatter, and depolarization using the algorithm described by Thorsen et al. 2015 and Thorsen and Fu 2015. This document provides a description of the FEX algorithm, its input and output data, and related details about the Raman lidar (RL) system.

54 ENVIRONMENTAL SCIENCES↗

Design of the American Wake Experiment (AWAKEN) field campaign

The American WAKE experimeNt (AWAKEN) is a multi-institutional collaborative field campaign, starting in March 2022, that will gather an unprecedented data set including both atmospheric observations and wind plant operational data. This comprehensive data set will be used to characterize the wind plant performance and turbine loading in different operational and atmospheric conditions and validate the use of different wind plant control strategies and simulation frameworks. An extensive field campaign like AWAKEN requires proper coordination and long-term planning to be successful. In this paper, we review the major activities planned during AWAKEN to provide information for current and future project partners. Specifically, we provide information about the project sites, their planned instruments, and how these will relate to the scientific objectives of the overall AWAKEN project.

17 WIND ENERGY↗

rlproffex1thor.c0

Implementation of feature detection and extinction retrieval algorithms developed by Tyler Thorsen

54 ENVIRONMENTAL SCIENCES↗

rlproffexext1thor.c0

Implementation of feature detection and extinction retrieval algorithms developed by Tyler Thorsen

54 ENVIRONMENTAL SCIENCES↗

rlproffexaux1thor.c0

Implementation of feature detection and extinction retrieval algorithms developed by Tyler Thorsen

54 ENVIRONMENTAL SCIENCES↗

rlproffexcnt1thor.c0

Implementation of feature detection and extinction retrieval algorithms developed by Tyler Thorsen

54 ENVIRONMENTAL SCIENCES↗

Rapid growth of anthropogenic organic nanoparticles greatly alters cloud life cycle in the Amazon rainforest

Aerosol-cloud interactions remain uncertain in assessing climate change. While anthropogenic activities produce copious aerosol nanoparticles smaller than 10 nanometers, they are too small to act as efficient cloud condensation nuclei (CCN). The mechanisms responsible for particle growth to CCN-relevant sizes are poorly understood. Here, we present aircraft observations of rapid growth of anthropogenic nanoparticles downwind of an isolated metropolis in the Amazon rainforest. Model analysis reveals that the sustained particle growth to CCN sizes is predominantly caused by particle-phase diffusion-limited partitioning of semivolatile oxidation products of biogenic hydrocarbons. Cloud-resolving numerical simulations show that the enhanced CCN concentrations in the urban plume substantially alter the formation of shallow convective clouds, suppress precipitation, and enhance the transition to deep convective clouds. The proposed nanoparticle growth mechanism, expressly enabled by the abundantly formed semivolatile organics, suggests an appreciable impact of anthropogenic aerosols on cloud life cycle in previously unpolluted forests of the world.

54 ENVIRONMENTAL SCIENCES↗

dlmcfpt.c1

The DLMC VAP uses inertial data from the ARM NAV system to transform the Doppler lidar beam angles (az and el) from the lidar's frame of reference to an Earth-fixed frame such the azimuth angle is measured clockwise from true north and the elevation angle is measured from the local horizon. Additionally, the VAP compensates the observed radial (air) velocity data for the effects of the platform velocity (i.e. corrected_radial_velocity = observed_radial_velocity-platform_radial_velocity). The VAP was developed specifically for MOSAiC. The dlmcfpt.c1 product contains the fixed point, or staring data. The dlmcusr.c1 product contains a user defined scan which is anything the operator wants it to be.

54 ENVIRONMENTAL SCIENCES↗

dlmcusr.c1

The DLMC VAP uses inertial data from the ARM NAV system to transform the Doppler lidar beam angles (az and el) from the lidar's frame of reference to an Earth-fixed frame such the azimuth angle is measured clockwise from true north and the elevation angle is measured from the local horizon. Additionally, the VAP compensates the observed radial (air) velocity data for the effects of the platform velocity (i.e. corrected_radial_velocity = observed_radial_velocity-platform_radial_velocity). The VAP was developed specifically for MOSAiC. The dlmcfpt.c1 product contains the fixed point, or staring data. The dlmcusr.c1 product contains a user defined scan which is anything the operator wants it to be.

54 ENVIRONMENTAL SCIENCES↗

dlfpt.a1

This is one of the output datastreams for Doppler Lidar ingest on motion platform

54 ENVIRONMENTAL SCIENCES↗

dlusr.a1

This is one of the output datastreams for Doppler Lidar ingest on motion platform

54 ENVIRONMENTAL SCIENCES↗

Simulation of Continental Shallow Cumulus Populations Using an Observation-Constrained Cloud-System Resolving Model

Continental shallow cumulus (ShCu) clouds observed on 30 August 2016 during the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) field campaign are simulated by using an observation-constrained cloud-system resolving model. On this day, ShCu forms over Oklahoma and southern Kansas and some of these clouds transition to deeper, precipitating convection during the afternoon. We apply a four-dimensional ensemble-variational (4DEnVar) hybrid technique in the Community Gridpoint Statistical Interpolation (GSI) system to assimilate operational data sets and unique boundary layer measurements including a Raman lidar, radar wind profilers, radiosondes, and surface stations collected by the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) atmospheric observatory into the Weather Research and Forecasting (WRF) model to ascertain how improved environmental conditions can influence forecasts of ShCu populations and the transition to deeper convection. Independent observations from aircraft, satellite, as well as ARM's remote sensors are used to evaluate model performance in different aspects. Several model experiments are conducted to identify the impact of data assimilation (DA) on the prediction of clouds evolution. The analyses indicate that ShCu populations are more accurately reproduced after DA in terms of cloud initiation time and cloud base height, which can be attributed to an improved representation of the ambient meteorological conditions and the convective boundary layer. Extending the assimilation to 18 UTC (local noon) also improved the simulation of shallow-to-deep transitions of convective clouds.

54 ENVIRONMENTAL SCIENCES↗

Doppler LIDAR Motion-corrected Wind Speed and Direction Profiles VAP

The dlmcprof-wind VAP contains profiles of wind speed and direction that are computed using motion-corrected Doppler lidar data from the dlmc VAP. The dlmcprof-wind VAP was specifically developed to process scanning data acquired by the ARM Doppler lidar aboard the Polarstern during the MOSAiC campaign.

54 ENVIRONMENTAL SCIENCES↗

Overview of the HI-SCALE Field Campaign: A New Perspective on Shallow Convective Clouds

Shallow convective clouds are common, occurring over many areas of the world, and are an important component in the atmospheric radiation budget. In addition to synoptic and mesoscale meteorological conditions, land-atmosphere interactions and aerosol-radiation-cloud interactions can influence the formation of shallow clouds and their properties. However, these processes exhibit large spatial and temporal variability and occur at the sub-grid scale for all climate and operational forecast models and must be represented by parameterizations. Uncertainties in shallow cloud parameterization predictions arise from many sources, including insufficient coincident data needed to adequately represent the coupling of cloud macrophysical and microphysical properties with inhomogeneity in the surface layer, boundary layer, and aerosol properties. Predictions in the transition of shallow to deep convection and the onset of precipitation are also affected by errors in simulated shallow clouds. Coincident data is a key factor needed to achieve a more complete understanding of the lifecycle of shallow convective clouds and to develop improved model parameterizations. To address these issues, the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) campaign was conducted near the Atmospheric Radiation and Measurement (ARM) Southern Great Plains site in north-central Oklahoma during 2016. We describe the scientific objectives of HI-SCALE as well as the experimental approach, the overall weather conditions during the campaign, and preliminary findings from the measurements. Finally, we discuss the remaining scientific gaps in our understanding of shallow clouds that can be addressed by analysis and modeling studies that use HI-SCALE data including: the effects of heterogeneous land-use, vegetation, and soil moisture conditions on boundary layer mixing and consequently cloud formation; factors that contribute to the transition of shallow to deep convection; the role of cloud population on

Fast, Jerome D.↗

Raman Lidar Water Vapor Mixing Ratio and Temperature Value-Added Products

This report describes the methods used to estimate profiles of water vapor mixing ratio (WVMR) and temperature from the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) user facility Raman lidars (RL). This includes a description of the equations and the calibration methods that are used, as well as the output datastreams and variable names. We begin with an overview of the ARM RL systems, with a focus on the detection channels used for the WVMR and temperature measurements.

54 ENVIRONMENTAL SCIENCES↗

Demonstration of Vaisala Prototype Differential Absorption Lidar (DIAL) Field Campaign Report

Continuous water vapor profiling within the atmospheric boundary layer is a major unmet measurement requirement for improving weather analysis and prediction. Humidity profile information can be used in mesoscale numerical models for severe weather prediction, flash flood prediction, energy management, and other applications. The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility has conducted several experiments at its Southern Great Plains (SGP) observatory in North Central Oklahoma to test and develop techniques for tropospheric water vapor measurements (Turner et al. 2016). This campaign concentrated on a new compact water vapor DIAL (DIfferential Absorption Lidar) instrument that the instrument manufacturer Vaisala has recently developed using a ceilometer-type telescope design (Dabberdt 2016, Roininen,2017). The DIAL system uses eye-safe class 1M semiconductor laser sources in the sub-micron wavelength range. The instrument reports water vapor mixing ratio profiles up to 3000 m within the atmospheric boundary layer, or up to the cloud base, whichever is lower. The purpose of the campaign was to test the Vaisala DIAL prototype (Figure 1) in high-humidity convective conditions at the ARM SGP site, comparing measurements against other instrumentation at the site (Münkel and Roininen 2017). Comparisons were made against Raman lidar and RS92 radiosonde observations of water vapor mixing ratio profiles. The same DIAL prototype has previously been tested in campaigns in Central and Northern Europe (Roininen et al. 2016). The ARM campaign was a collaboration between Vaisala and researchers from Pacific Northwest National Laboratory (PNNL), National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL), and National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL). The DIAL was located next to the Raman lidar at the ARM SGP site (Figure 2). Two Vaisala employees visited the site for the installation work, which was carried out on May 15, 2017.

Southern Great Plains, Raman lidar, planetary boun↗