Comment on egusphere-2022-1405

Surface bi-directional reflectance distribution function (BRDF) and albedo properties are retrieved over the Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SGP) area. A landcover-based fitting approach is employed by using a newly developed landcover classification map and the MODIS 10-day surface reflectance product (MOD09). The surface albedo derived by this method is validated against other satellite systems (e.g. Landsat-7 and MISR) and ground measurements made by an ASD spectroradiometer. Our results show good agreements between the datasets in general. The advantages of this method include the ability to capture rapid changes in surface properties and an improved performance over other methods under a frequent presence of clouds. Results indicate that the developed landcover-based fitting methodology is valuable for generating spatially and temporally complete surface albedo and BRDF maps using MODIS observations.

Raman lidar water vapor and aerosol extinction profiles acquired during the daytime over the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in northern Oklahoma (36.606 N, 97.50 W, 315 m) are evaluated using profiles measured by in situ and remote sensing instruments deployed during the May 2003 Aerosol Intensive Operations Period (IOP). The automated algorithms used to derive these profiles from the Raman lidar data were first modified to reduce the adverse effects associated with a general loss of sensitivity of the Raman lidar since early 2002. The Raman lidar water vapor measurements, which are calibrated to match precipitable water vapor (PWV) derived from coincident microwave radiometer (MWR) measurements were, on average, 5–10% (0.3–0.6 g/m3) higher than the other measurements. Some of this difference is due to out‐of‐date line parameters that were subsequently updated in the MWR PWV retrievals. The Raman lidar aerosol extinction measurements were, on average, about 0.03 km−1 higher than aerosol measurements derived from airborne Sun photometer measurements of aerosol optical thickness and in situ measurements of aerosol scattering and absorption. This bias, which was about 50% of the mean aerosol extinction measured during this IOP, decreased to about 10% when aerosol extinction comparisons were restricted to aerosol extinction values larger than 0.15 km−1. The lidar measurements of the aerosol extinction/backscatter ratio and airborne Sun photometer measurements of the aerosol optical thickness were used along with in situ measurements of the aerosol size distribution to retrieve estimates of the aerosol single scattering albedo (ωo) and the effective complex refractive index. Retrieved values of ωo ranged from (0.91–0.98) and were in generally good agreement with ωo derived from airborne in situ measurements of scattering and absorption. Elevated aerosol layers located between about 2.6 and 3.6 km were observed by the Raman lidar on 25 and 27 May. The airborne measurements and lidar retrievals indicated that these layers, which were likely smoke produced by Siberian forest fires, were primarily composed of relatively large particles (reff ∼ 0.23 μm) and that the layers were relatively nonabsorbing (ωo ∼ 0.96–0.98). Preliminary results show that major modifications that were made to the Raman lidar system during 2004 have dramatically improved the sensitivity in the aerosol and water vapor channels and reduced random errors in the aerosol scattering ratio and water vapor retrievals by an order of magnitude.

Abstract. This study presents and applies three separate processing methods to improve high-order moments estimated from 35 GHz (Ka band) vertically pointing radar Doppler velocity spectra. The first processing method removes Doppler-shifted ground clutter from spectra collected by a US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Ka-band zenith pointing radar (KAZR) deployed at Oliktok Point (OLI), Alaska. Ground clutter resulted from multiple pathways through antenna side lobes and reflections off a rotating scanning radar antenna located 2 m away from KAZR, which caused Doppler shifts in ground clutter returns from stationary targets 2.5 km away. After removing clutter in the recorded velocity spectra, the second processing method identifies multiple separate and sub-peaks in the spectra and estimates high-order moments for each peak. Multiple peaks and high-order moments were estimated for both original 2 and 15 s averaged spectra. The third processing step improves the spectrum variance, skewness, and kurtosis estimates by removing velocity variability due to turbulent broadening during 15 s averaging intervals. Applying the multiple peak processing to Doppler velocity spectra during liquid-only clouds can identify cloud and drizzle particles and during mixed-phase clouds can identify liquid cloud and frozen hydrometeors. Consistent with previous studies, this work found that spectrum skewness assuming only a single spectral peak was a good indicator of two hydrometeor populations (for example, cloud and drizzle particles) being present in the radar pulse volume. Yet, after dividing the spectrum into multiple peaks, velocity spectrum skewness for individual peaks is near zero, indicating nearly symmetric peaks. This suggests that future studies should use velocity skewness of single-peak spectra as an indicator of possible multiple hydrometeor populations and then use multiple-peak moments for quantitative studies. Three future activities will continue this work. First, KAZR spectra from several ARM sites have been processed and are available in the ARM archive as a principal investigator (PI) product. ARM programmers are evaluating these processing methods as part of future multiple-peak products generated by ARM. Third, MATLAB code generating the Oliktok Point products has been uploaded as supplemental material for public dissemination.

This paper presents an overview of the Lower Atmospheric Boundary Layer Experiment (LABLE), which included two measurement campaigns conducted at the Atmospheric Radiation Measurement (ARM) Program Southern Great Plains site in Oklahoma during 2012 and 2013. LABLE was conducted as a collaborative effort between the University of Oklahoma (OU), the National Severe Storms Laboratory, Lawrence Livermore National Laboratory (LLNL), and the ARM program. LABLE can be considered unique in that it was designed as a multiphase, low-cost, multiagency collaboration. Graduate students served as principal investigators and took the lead in designing and conducting experiments aimed at examining boundary layer processes. The main objective of LABLE was to study turbulent phenomena in the lowest 2 km of the atmosphere over heterogeneous terrain using a variety of novel atmospheric profiling techniques. Several instruments from OU and LLNL were deployed to augment the suite of in situ and remote sensing instruments at the ARM site. The complementary nature of the deployed instruments with respect to resolution and height coverage provides a near-complete picture of the dynamic and thermodynamic structure of the atmospheric boundary layer. This paper provides an overview of the experiment including 1) instruments deployed, 2) sampling strategies, 3) parameters observed, and 4) student involvement. To illustrate these components, the presented results focus on one particular aspect of LABLE: namely, the study of the nocturnal boundary layer and the formation and structure of nocturnal low-level jets. During LABLE, low-level jets were frequently observed and they often interacted with mesoscale atmospheric disturbances such as frontal passages.

This document provides information about the many reports and other materials made available by the US Department of Energy`s (DOE`s) Global Change Research Program (GCRP). It is divided into nine sections plus author and title indexes: Section A -- US Department of Energy Global Change Research Program research plans and summaries; Section B -- US Department of Energy Global Change Research Program technical reports; Section C -- US Department of energy Atmospheric Radiation Measurement (ARM) program reports; Section D -- Other US Department of Energy reports; Section E -- CDIAC reports; Section F -- CDIAC numeric data and computer model distribution; Section G -- other data sets distributed by CDIAC; Section H -- USDA reports on response of vegetation to carbon dioxide; Section I -- other publications.

The Atomic Energy Act, as amended, authorizes the United States (U.S.) Department of Energy (DOE) and its predecessor agencies to distribute nuclear materials to public or private institutions for the purposes of education as well as research and development. Significant transformations throughout the nuclear industry have led to changes in programmatic responsibility for loaned nuclear materials. DOE has established several programs to catalog, transfer ownership, retrieve, and/or dispose of these loaned nuclear materials. The variety of loaned nuclear material types as well as operational and regulatory variations between facility licensees have created unique challenges for the retrieval and dispositioning processes. These include packaging and transportation, confirmation of regulatory jurisdiction, property transfer, and disposal of sources with no remaining economic value. This paper explores the methods and actions taken by DOE to address these challenges. Lessons learned and the best practices identified from these programs are also presented.

The objective of this paper is to assess the accuracy of the Semi-Analytical CloUd Retrieval Algorithm (SACURA) that retrieves cloud-top heights (CTHs) using hyperspectral SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) onboard Environmental Satellite measurements for overcast single-layer cloud fields. Intercomparisons with ground-based 35-GHz millimeter wave cloud radar CTHs were performed for 14 dates during 2003-2007 at the U.S. Atmospheric Radiation Measurement (ARM) program Southern Great Plains site (36.6deg N, 97.5deg W). In addition, for some of these dates, European Space Agency MEdium Resolution Imaging Spectrometer (MERIS) and the NASA-TERRA Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-top pressure retrievals were also collected, transformed into CTHs using nearby ARM radiosonde profiles, and compared with the SACURA SCIAMACHY and radar retrievals. The accuracy of the SACURA-SCIAMACHY CTH retrievals is better than 0.34 km for low-level clouds and 2.22 km for high-level clouds with an underestimate in CTH on average for all clouds. The average bias in SCIAMACHY CTHs was about 0.07 km for low clouds and about 0.5 km for high-level clouds. Both MODIS and MERIS slightly overestimated the CTHs of low-level clouds by 300 m, with an uncertainty better than 1 km. However, although MODIS accuracy for high-level clouds is close to SCIAMACHY, MERIS CTHs were significantly underestimated for these fairly optically thick cases.

At the close of each fiscal year, the US Department of Energy (DOE) Sustainability Performance Office (SPO) issues guidance documents and technical resource aids/tools necessary for DOE sites and national laboratories to complete sustainability reporting requirements. SPO is part of the DOE Office of Asset Management. As required by DOE Order 436.1A, Departmental Sustainability, each site develops and commits to an annual site sustainability plan (SSP) that identifies its respective contribution toward meeting DOE’s sustainability goals. SPO collects and compiles information reported by each site to develop an agency-wide sustainability report and implementation plan, which is used to report DOE sustainability progress to the federal government as required by all major federal agencies. DOE launched a formal Sustainability Office and annual SSP process in 2011. Each year, Oak Ridge National Laboratory (ORNL), in concert with the DOE Office of Science (SC), provides the resources essential to fulfill its commitment to deliver a complete and accurate SSP and quality performance data for entry into the DOE Sustainability Dashboard managed by SPO. The performance data entered by each DOE site are then combined to disclose the progress of each DOE program office and are further combined to show comprehensive progress for the agency. The Office of Asset Management assists program offices in sustaining their missions, freeing up resources by reducing waste, avoiding excess expenditure on utilities, maximizing productivity, and improving the efficiency of facilities and processes. By focusing on mission needs, programs and associated DOE sites can help the agency meet its sustainability goals as outlined in federal statutory and regulatory requirements. In FY 2022, the SSP Guidance/Instructions (US Department of Energy, Sustainability Performance Office) was updated to capture requirements from Executive Order (EO) 14008, Tackling the Climate Crisis at Home and Abroad; the Energy Act of 2020 (EAct 20); actions outlined in DOE’s Climate Adaptation and Resilience Plan and Sustainability Plan; and EO 14057, Catalyzing Clean Energy Industries and Jobs Through Federal Sustainability. Updates in SSP guidance help to minimize and streamline reporting while simultaneously addressing updated federal requirements. Per DOE, each SSP should provide an overview of the site’s planned actions and of efforts and accomplishments during the reporting period. SPO collects and compiles information reported by each site to develop DOE’s Annual Sustainability Report, Climate Adaptation and Resilience Plan, and Annual Energy Management Report to Congress. The agency goal has been to lower the reporting burden for sites and increase and improve the consistency of information available to decision-makers, allowing them to better identify projects and potential for increased efficiency and to reduce waste, lower emissions, and enhance operational resilience. Sites may elect to produce more polished publications for their leadership and stakeholders, but this step is no longer required. The ORNL SSP narrative report (this document) and the reporting of DOE SPO Sustainability Dashboard performance data is a collaborative effort of approximately 30 subject matter experts (SMEs) from ORNL facility management, mission support, and research divisions. Annually, these associates come together to provide a report that can be used by DOE to demonstrate continued agency progress in energy efficiency and sustainable federal operations.

The properties of midlatitude cirrus clouds are examined using one year of continuous vertically pointing millimeter-wave cloud radar data collected at the Atmospheric Radiation Measurement Program Southern Great Plains site in Oklahoma. The goal of this analysis is to present the cloud characteristics in a manner that will aid in the evaluation and improvement of cirrus parameterizations in large-scale models. Using a temperature- and radar reflectivity–based definition of cirrus, the occurrence frequency of cirrus, the vertical location and thickness of cirrus layers, and other fundamental statistics are examined. Also the bulk microphysical properties of optically thin cirrus layers that occur in isolation from other cloud layers are examined. During 1997, it is found that cirrus were present 22% of the time, had a mean layer thickness of 2.0 km, and were most likely to occur in the 8.5–10-km height range. On average, the cirrus clouds tended to be found in layers in which the synoptic-scale v...

Clouds are a central focus of the U.S. Department of Energy (DOE)’s Atmospheric System Research (ASR) program and Atmospheric Radiation Measurement (ARM) Climate Research Facility, and more broadly are the subject of much investigation because of their important effects on atmospheric radiation and, through feedbacks, on climate sensitivity. Significant progress has been made by moving from a vertically pointing (“soda-straw”) to a three-dimensional (3D) view of clouds by investing in scanning cloud radars through the American Recovery and Reinvestment Act of 2009. Yet, because of the physical nature of radars, there are key gaps in ARM's cloud observational capabilities. For example, cloud radars often fail to detect small shallow cumulus and thin cirrus clouds that are nonetheless radiatively important. Furthermore, it takes five to twenty minutes for a cloud radar to complete a 3D volume scan and clouds can evolve substantially during this period. Ground-based stereo-imaging is a promising technique to complement existing ARM cloud observation capabilities. It enables the estimation of cloud coverage, height, horizontal motion, morphology, and spatial arrangement over an extended area of up to 30 by 30 km at refresh rates greater than 1 Hz (Peng et al. 2015). With fine spatial and temporal resolution of modern sky cameras, the stereo-imaging technique allows for the tracking of a small cumulus cloud or a thin cirrus cloud that cannot be detected by a cloud radar. With support from the DOE SunShot Initiative, the Principal Investigator (PI)’s team at Brookhaven National Laboratory (BNL) has developed some initial capability for cloud tracking using multiple distinctly located hemispheric cameras (Peng et al. 2015). To validate the ground-based cloud stereo-imaging technique, the cloud stereo-imaging field campaign was conducted at the ARM Facility’s Southern Great Plains (SGP) site in Oklahoma from July 15 to December 24. As shown in Figure 1, the cloud stereo-imaging system consisted of two inexpensive high-definition (HD) hemispheric cameras (each cost less than $1,500) and ARM’s Total Sky Imager (TSI). Together with other co-located ARM instrumentation, the campaign provides a promising opportunity to validate stereo-imaging-based cloud base height and, more importantly, to examine the feasibility of cloud thickness retrieval for low-view-angle clouds.

DOE complies with all Federal regulations governing radioactive material shipments to maintain an excellent safety record. The US Department of Energy (DOE) uses radioactive material for National defense and research and development activities and is a major shipper of this material. DOE shipments go through almost all 50 states in both government and commercial vehicles via air, highway, rail, and water. DOE manages the transportation of the following: uranium ore from mines to processing facilities where the uranium is enriched and prepared as reactor fuel; reactor fuel to nuclear reactors; materials for research in new energy technologies; special nuclear materials for defense purposes; reactor byproducts to research laboratories, industrial plants, and medical institutions; and radioactive waste to interim storage and disposal sites. As with many substances, potential hazards arise in transporting radioactive material, and DOE takes stringent precautions to minimize and eliminate risk. DOE packages and transports according to the Department of Transportation's (DOT) Title 49 Code of Federal Regulations, Part 173 (49 CFR 173). In addition, DOE has adopted the packaging standards of the Nuclear Regulatory Commission (NRC). These regulations and standards are implemented through DOE safety and operational directives called DOE Orders. The safety record for shipping radioactive material clearly shows that the protection of the public and the environment is of the highest priority. Strict enforcement of regulations and ongoing research show DOE's commitment to maintain this excellent record. 21 figs.

In the field of semiconductor quantum dot spin qubits, there is growing interest in leveraging the unique properties of hole-carrier systems and their intrinsically strong spin-orbit coupling to engineer novel spin qubits. In contrast to the weak spin-orbit interaction found in Si, strong spin-orbit coupling in Ge may allow purely electrical spin control using the electric field component of a microwave drive signal applied to a confinement gate, without the need for additional components such as microwave stripline antennas or micromagnets. A crucial aspect in the search for alternative semiconductor qubit host materials is the need to maintain the advantages of existing platforms such as Si: low disorder, long coherence times, extensibility, and semiconductor foundry compatibility. Recent advances in semiconductor heterostructure growth have made available high quality, undoped Ge/SiGe quantum wells that can serve as hosts for hole spin qubits. These quantum wells consist of a pure strained Ge layer flanked by Ge-rich SiGe layers above and below, grown by reduced pressure chemical vapor deposition. Isotopic enrichment is possible if required. The heavy hole charge carriers are characterized by a small effective mass m* ~ 0.08m 0 (about 2.4x lighter than for electrons in Si), high mobility μ ≥ 1E5 cm2/Vs, and highly anisotropic g-factors. The small effective mass should allow relatively large and easily-coupled quantum dots. The next-nearest light hole band is theoretically predicted to be on the order of ~ 100 meV below the heavy hole band. The p-orbital character of the hole wavefunction may provide an advantage in minimizing contact hyperfine interactions with nonzero-spin lattice nuclei. There is both theoretical and experimental evidence of a cubic Rashba-type spin-orbit interaction in this material, whose large strength is manifest as a spin-orbit length on the order of 1 micrometer. An additional advantage over Si is that the two-dimensional band structure of Ge quantum wells does not feature valley states, which can present difficulties for qubit operations. Here, we will describe our ongoing efforts to prepare spin qubits in this platform, including development of gated device architectures, device tuning protocols, and charge-sensing capabilities. Initial work focused on single-layer gate layouts, in which lithographically-defined single and double quantum dots were demonstrated at dilution refrigerator temperatures. Charging energies of ~ 1.7 meV were observed. These devices featured a broad and shallow potential landscape, and only a small number of holes could be confined to a quantum dot. Although adjacent quantum dots could be coupled to one another, this coupling was not easily tuned using this gate design. These limitations in the confinement and control of quantum dots motivated the subsequent adoption of multilayer gate-stack architectures, similar to what has been demonstrated in Si. Our three-layer devices feature gate electrodes designed for accumulation of holes, local depletion to form quantum dots, and selective isolation/screening of electric fields. Device structures feature Ti/Pt gates, ALD oxide dielectrics, and implanted ohmic contacts. Symmetrically constructed devices comprise two gated channels for quantum dot confinement, one to be used as the quantum dot under study and the other operated as a local charge sensor. By monitoring the conductance of the charge sensor as the quantum dot is tuned, we can remotely determine the dot’s occupation number, in principle down to the last hole. Iterative cycles of device fabrication and measurement, combined with numerical modeling, have allowed continuous improvements to the device design. Early three-layer device designs suffered from poor isolation between the upper and lower mirror-symmetric device channels. Numerical modeling showed (and measurements have confirmed) that an additional isolation gate could allow improved autonomy of the two channels while maintaining their electrostatic coupling needed for charge sensing. Ongoing, simulation-informed work to fine-tune the device geometry, as well as efforts toward a qubit demonstration, will be discussed. This work was funded, in part, by the Laboratory Directed Research and Development Program and performed, in part, at the Center for Integrated Nanotechnologies, an Office of Science User Facility operated for the US Department of Energy (DOE) Office of Science. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the US Department of Energy’s National Nuclear Security Administration under contract DE-NA-0003525. The views expressed in this article do not necessarily represent the views of the US Department of Energy or the United States Government. The work at NTU was supported by the Ministry of Science and Technology (107-2622-8-002-018-). Figure 1

Aerosol light absorption and scattering of solar radiation play an important role in the earth’s atmosphere in terms of direct and semi-direct radiative forcing. Optical parameters of importance to the US Department of Energy (DOE) climate models include absorption and scattering coefficients, single scattering albedo (SSA), absorption Angstrom exponents (AAE), and the asymmetry parameter (g). These parameters depend on aerosol size, shape and composition (refractive index), and are spectrally sensitive in the shortwave region. Additionally, these parameters have a complex dependency on the emission source, especially for carbonaceous aerosols. The DOE Atmospheric Radiation Measurement (ARM) user facility has deployed aerosol observing systems (AOS) containing several filter-based instruments to measure and constrain aerosol optical properties and related parameters at multiple sites worldwide. For measurement of aerosol light absorption, the AOS includes filter-based instruments (particle soot absorption photometer and tricolor absorption photometer) that infer particle-phase aerosol absorption coefficients at nominal red, green, and blue wavelength bands from the attenuation (ATN) of light passing through a particulate filter on which aerosols are deposited. Measurement of aerosol scattering is done in situ using nephelometers. By combining inferred absorption coefficients from filter-based ATN measurements and in situ scattering coefficients, value-added products (VAPs) such as SSA, AAE, and g are derived.

Abstract. Observational estimates of Kelvin wave momentum fluxes in the tropical lower stratosphere remain challenging. Here we extend a method based on linear wave theory to estimate daily time series of these momentum fluxes from high-resolution radiosonde data. Daily time series are produced for sounding sites operated by the US Department of Energy (DOE) and from the recent Dynamics of the Madden–Julian Oscillation (DYNAMO) field campaign. Our momentum flux estimates are found to be robust to different data sources and processing and in quantitative agreement with estimates from prior studies. Testing the sensitivity to vertical resolution, our estimated momentum fluxes are found to be most sensitive to vertical resolution greater than 1 km, largely due to overestimation of the vertical wavelength. Climatological analysis is performed over a selected 11-year span of data from DOE Atmospheric Radiation Measurement (ARM) radiosonde sites. Analyses of this 11-year span of data reveal the expected seasonal cycle of momentum flux maxima in boreal winter and minima in boreal summer, and variability associated with the quasi-biennial oscillation of maxima during easterly phase and minima during westerly phase. Comparison between periods with active convection that is either strongly or weakly associated with the Madden–Julian Oscillation (MJO) suggests that the MJO provides a nontrivial increase in the lowermost stratospheric momentum fluxes.

To better provide U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s disdrometer deployment strategy and support ARM precipitation-related projects, this study analyzes 18 months of drop size distribution (DSD) observations from six collocated disdrometers deployed at the ARM Southern Great Plains (SGP) site. Emphasis is placed on quantifying the uncertainties related to DSD and rainfall properties using different types of disdrometers and different pairing concepts. The instrument sampling errors are also discussed, which improves our understanding of instrument-specific impacts on rainfall measurements. The key findings are as follows: 1) All the disdrometers show consistent behaviors overall regarding accumulated precipitation, mean rainfall rate, DSD parameters, and radar reflectivity values; and 2) Strong agreement is shown between three disdrometer types in terms of their DSDs for mid-size drop range (D = 1 mm-4 mm). The two-dimensional video disdrometer performance meets expectations as the most accurate unit among all. The paired disdrometer shows a reduced statistical sampling error in terms of drop counts and other DSD properties. A concept of deploying two or more collocated disdrometers side by side is recommended for future ARM field campaigns.