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Macquarie Island Cloud and Radiation Experiment (MICRE) Field Campaign Report

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility, the Australian Antarctic Division (AAD), and the Australian Bureau of Meteorology (BOM) collaborated in deploying a variety of ground instrumentation to Macquarie Island between March 2016 and March 2018. Macquarie Island is located at 54.5° S, 158.9° E and is well situated for studying clouds over the Southern Ocean. The primary objective of the March 2016 to March 2018 deployment, hereafter the Macquarie Island Cloud and Radiation Experiment (MICRE), was to collect observations of surface radiation, cloud, precipitation, and aerosol properties. This report describes the instruments deployed and data sets collected, along with a summary of key data quality issues and information on some value-added products that are being developed to assist scientists in using the data.

54 ENVIRONMENTAL SCIENCES↗

Tower Water-Vapor Mixing Ratio Value-Added Product Report

The purpose of the Tower Water-Vapor Mixing Ratio (TWRMR) value-added product (VAP) is to calculate water-vapor mixing ratios at the 25-meter and 60-meter levels of the meteorological tower and also report best-estimate temperature, relative humidity, and pressure measurements at the 2-meter, 25-meter, and 60-meter levels at the Atmospheric Radiation Measurement (ARM) user facility Southern Great Plains (SGP) Central Facility. Because there are no barometric pressure sensors at the 25-meter and 60-meter levels on the tower, the hypsometric equation is used along with surface pressure values from the surface meteorological instrumentation (MET), the surface meteorological observation system (SMOS), or the temperature, humidity, wind, and pressure system (THWAPS) to derive barometric pressures at those altitudes (Ritsche 2008, 2011a, 2011b). After this is done, water-vapor mixing ratio can be calculated directly.

54 ENVIRONMENTAL SCIENCES↗

An Evaluation of the Spectral Irradiance Data from the NSRDB

A recent effort by the National Renewable Energy Laboratory (NREL) has led to a new radiative transfer model, the Fast All-sky Radiation Model for Solar applications with Narrowband Irradiances on Tilted surfaces (FARMS-NIT), to efficiently compute spectral irradiances in the plane-of-array (POA). This model has been implemented in the National Solar Radiation Data Base (NSRDB) to provide photovoltaic (PV) resource in both narrowband and broadband wavelengths. This study conducts an evaluation of the spectral irradiances from the PV Resource dataset using surface-based observations at NREL’s Solar Radiation Research Laboratory (SRRL) and University of Oregon (UO). The results demonstrate that the PV resource has a generally good agreement with the long-term observations in both clear-sky and cloudy-sky conditions. Further research is needed to reduce the overestimation of visible irradiances in clear sky conditions and underestimation of near-infrared irradiances in cloudy-sky conditions.

14 SOLAR ENERGY↗

Advanced Precipitation and Boundary Layer Data Products Derived from ARM Radar Wind Profilers

This research project was successful in delivering on four main objectives. First, software was developed to accurately calculate 915-MHz radar wind profiler (RWP) spectrum moments from the recorded Doppler velocity power spectra. Second, software was developed to calibrate the RWP reflectivity factor using collocated surface disdrometer observations. Third, the Python processing code was documented and given to the ARM Infrastructure to produce ARM ‘b level’ calibrated RWP products. Fourth, calibrated RWP products were uploaded to the ARM Archive as PI Products for 10 years of SGP RWP observations and for GoAmazon and TRACER field campaign RWP observations. In addition to working with RWP observations, this research project also worked with KAZR observations to distinguish insects from boundary layer clouds to help improve the ARSCL cloud mask product. The PI worked with senior and early career ARM funded scientists at BNL exploring how to include calibrated RWP moments into future versions of the ARSCL product.

54 ENVIRONMENTAL SCIENCES↗

Measure Effects of Molten Halide Salt on Creep Rupture Lifetime for 316H, 709 and 617

Ongoing commercialization of different molten salt reactor concepts can considerably benefit from quantitative information on the impact of molten halide salts on the engineering properties such as creep and fatigue strength of materials of interest. Limited legacy data from the molten salt reactor experiment (MSRE) program showed a significant reduction in creep rupture strength of a Ni-base alloy in molten fluoride salt. This task evaluated the creep behavior of candidate structural materials 316H, 709 and 617 for advanced nuclear reactors under molten halide salt environments at 650, 700 and 750°C respectively. Creep tests were conducted in air, Ar, fluoride (FLiNaK) and chloride (NaCl-MgCl 2 ) salts. The molten salt environment caused a 50% reduction in creep rupture lifetime for 316H in FLiNaK and an 80% reduction in creep rupture lifetime in NaCl-MgCl 2 compared to air exposures. The molten fluoride salt environment resulted in almost a 90% and 50% reduction in creep rupture time for 709 and 617 irrespective of the cover gas environment (air and Ar). Significant differences in the compositional changes between the salt- and air-facing surfaces were observed in the alloy subsurface which might have potentially lead to formation of phases detrimental to the creep behavior.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Provider - University of Washington - Raw Data

GOES satellite, WSR-88D radar, sounding balloon, surface weather observation and mesoscale model data from the area within, up, and downstream of the study area for use in event logging procedures and case study investigations.

17 WIND ENERGY↗

Provider - University of Washington - Reviewed Data

GOES satellite, WSR-88D radar, sounding balloon, surface weather observation and mesoscale model data from the area within, up, and downstream of the study area for use in event logging procedures and case study investigations.

17 WIND ENERGY↗

Wind Resource Assessment for Alaska’s Offshore Regions: Validation of a 14-Year High-Resolution WRF Data Set

Offshore wind resource assessments for the conterminous U.S. and Hawai’i have been developed before, but Alaska’s offshore wind resource has never been rigorously assessed. Alaska, with its vast coastline, presents ample potential territory in which to build offshore wind farms, but significant challenges have thus far limited Alaska’s deployment of utility-scale wind energy capacity to a modest 62 MW (or approximately 2.7% of the state’s electric generation) as of this writing, all in land-based wind farms. This study provides an assessment of Alaska’s offshore wind resource, the first such assessment for Alaska, using a 14-year, high-resolution simulation from a numerical weather prediction and regional climate model. This is the longest-known high-resolution model data set to be used in a wind resource assessment. Widespread areas with relatively shallow ocean depth and high long-term average 100-m wind speeds and estimated net capacity factors over 50% were found, including a small area near Alaska’s population centers and the largest transmission grid that, if even partially developed, could provide the bulk of the state’s energy needs. The regional climate simulations were validated against available radiosonde and surface wind observations to provide the confidence of the model-based assessment. The model-simulated wind speed was found to be skillful and with near-zero average bias (−0.4–0.2 m s−1) when averaged over the domain. Small sample sizes made regional validation noisy, however.

17 WIND ENERGY↗

STAIR 2.0: A Generic and Automatic Algorithm to Fuse Modis, Landsat, and Sentinel-2 to Generate 10 m, Daily, and Cloud-/Gap-Free Surface Reflectance Product

Remote sensing datasets with both high spatial and high temporal resolution are critical for monitoring and modeling the dynamics of land surfaces. However, no current satellite sensor could simultaneously achieve both high spatial resolution and high revisiting frequency. Therefore, the integration of different sources of satellite data to produce a fusion product has become a popular solution to address this challenge. Many methods have been proposed to generate synthetic images with rich spatial details and high temporal frequency by combining two types of satellite datasets—usually frequent coarse-resolution images (e.g., MODIS) and sparse fine-resolution images (e.g., Landsat). In this paper, we introduce STAIR 2.0, a new fusion method that extends the previous STAIR fusion framework, to fuse three types of satellite datasets, including MODIS, Landsat, and Sentinel-2. In STAIR 2.0, input images are first processed to impute missing-value pixels that are due to clouds or sensor mechanical issues using a gap-filling algorithm. The multiple refined time series are then integrated stepwisely, from coarse- to fine- and high-resolution, ultimately providing a synthetic daily, high-resolution surface reflectance observations. We applied STAIR 2.0 to generate a 10-m, daily, cloud-/gap-free time series that covers the 2017 growing season of Saunders County, Nebraska. Moreover, the framework is generic and can be extended to integrate more types of satellite data sources, further improving the quality of the fusion product. View Full-Text

47 OTHER INSTRUMENTATION↗

Temporal Evolution of the High-energy Irradiation and Water Content of TRAPPIST-1 Exoplanets

The ultracool dwarf star TRAPPIST-1 hosts seven Earth-size transiting planets, some of which could harbor liquid water on their surfaces. Ultraviolet observations are essential to measuring their high-energy irradiation and searching for photodissociated water escaping from their putative atmospheres. Our new observations of the TRAPPIST-1 Ly α line during the transit of TRAPPIST-1c show an evolution of the star emission over three months, preventing us from assessing the presence of an extended hydrogen exosphere. Based on the current knowledge of the stellar irradiation, we investigated the likely history of water loss in the system. Planets b to d might still be in a runaway phase, and planets within the orbit of TRAPPIST-1g could have lost more than 20 Earth oceans after 8 Gyr of hydrodynamic escape. However, TRAPPIST-1e to h might have lost less than three Earth oceans if hydrodynamic escape stopped once they entered the habitable zone (HZ). We caution that these estimates remain limited by the large uncertainty on the planet masses. They likely represent upper limits on the actual water loss because our assumptions maximize the X-rays to ultraviolet-driven escape, while photodissociation in the upper atmospheres should be the limiting process. Late-stage outgassing could also have contributed significant amounts of water for the outer, more massive planets after they entered the HZ. While our results suggest that the outer planets are the best candidates to search for water with the JWST , they also highlight the need for theoretical studies and complementary observations in all wavelength domains to determine the nature of the TRAPPIST-1 planets and their potential habitability.

79 ASTRONOMY AND ASTROPHYSICS↗

Estimating global and North American methane emissions with high spatial resolution using GOSAT satellite data

We use 2009–2011 space-borne methane observations from the Greenhouse Gases Observing SATellite (GOSAT) to estimate global and North American methane emissions with 4° × 5° and up to 50 km × 50 km spatial resolution, respectively. GEOS-Chem and GOSAT data are first evaluated with atmospheric methane observations from surface and tower networks (NOAA/ESRL, TCCON) and aircraft (NOAA/ESRL, HIPPO), using the GEOS-Chem chemical transport model as a platform to facilitate comparison of GOSAT with in situ data. This identifies a high-latitude bias between the GOSAT data and GEOS-Chem that we correct via quadratic regression. Our global adjoint-based inversion yields a total methane source of 539 Tg a −1 with some important regional corrections to the EDGARv4.2 inventory used as a prior. Results serve as dynamic boundary conditions for an analytical inversion of North American methane emissions using radial basis functions to achieve high resolution of large sources and provide error characterization. We infer a US anthropogenic methane source of 40.2–42.7 Tg a −1 , as compared to 24.9–27.0 Tg a −1 in the EDGAR and EPA bottom-up inventories, and 30.0–44.5 Tg a −1 in recent inverse studies. Our estimate is supported by independent surface and aircraft data and by previous inverse studies for California. We find that the emissions are highest in the southern–central US, the Central Valley of California, and Florida wetlands; large isolated point sources such as the US Four Corners also contribute. Using prior information on source locations, we attribute 29–44 % of US anthropogenic methane emissions to livestock, 22–31 % to oil/gas, 20 % to landfills/wastewater, and 11–15 % to coal. Wetlands contribute an additional 9.0–10.1 Tg a −1 .

54 ENVIRONMENTAL SCIENCES↗

Open cells exhibit weaker entrainment of free-tropospheric biomass burning aerosol into the south-east Atlantic boundary layer

This work presents synergistic satellite, airborne and surface-based observations of a pocket of open cells (POC) in the remote south-east Atlantic. The observations were obtained over and upwind of Ascension Island during the CLouds and Aerosol Radiative Impacts and Forcing (CLARIFY) and the Layered Smoke Interacting with Clouds (LASIC) field experiments. A novel aspect of this case study is that an extensive free-tropospheric biomass burning aerosol plume that had been transported from the African continent was observed to be in contact with the boundary layer inversion over the POC and the surrounding closed cellular cloud regime. The in situ measurements show marked contrasts in the boundary layer thermodynamic structure, cloud properties, precipitation and aerosol conditions between the open cells and surrounding overcast cloud field. The data demonstrate that the overlying biomass burning aerosol was mixing down into the boundary layer in the stratocumulus cloud downwind of the POC, with elevated carbon monoxide, black carbon mass loadings and accumulation-mode aerosol concentrations measured beneath the trade-wind inversion. The stratocumulus cloud in this region was moderately polluted and exhibited very little precipitation falling below cloud base. A rapid transition to actively precipitating cumulus clouds and detrained stratiform remnants in the form of thin quiescent veil clouds was observed across the boundary into and deep within the POC. The subcloud layer in the POC was much cleaner than that in the stratocumulus region. The clouds in the POC formed within an ultra-clean layer (accumulation-mode aerosol concentrations of approximately a few cm -3 ) in the upper region of the boundary layer, which was likely to have been formed via efficient collision–coalescence and sedimentation processes. Enhanced Aitken-mode aerosol concentrations were also observed intermittently in this ultra-clean layer, suggesting that new particle formation was taking place. Across the boundary layer inversion and immediately above the ultra-clean layer, accumulation-mode aerosol concentrations were ~1000 cm -3 . Importantly, the air mass in the POC showed no evidence of elevated carbon monoxide over and above typical background conditions at this location and time of year. As carbon monoxide is a good tracer for biomass burning aerosol that is not readily removed by cloud processing and precipitation, it demonstrates that the open cellular convection in the POC is not able to entrain large quantities of the free-tropospheric aerosol that was sitting directly on top of the boundary layer inversion. This suggests that the structure of the mesoscale cellular convection may play an important role in regulating the transport of aerosol from the free troposphere down into the marine boundary layer. We then develop a climatology of open cellular cloud conditions in the south-east Atlantic from 19 years of September Moderate Resolution Imaging Spectroradiometer (MODIS) Terra imagery. This shows that the maxima in open cell frequency (> 0.25) occurs far offshore and in a region where subsiding biomass burning aerosol plumes may often come into contact with the underlying boundary layer cloud. If the results from the observational case study applied more broadly, then the apparent low susceptibility of open cells to free-tropospheric intrusions of additional cloud condensation nuclei could have some important consequences for aerosol–cloud interactions in the region.

54 ENVIRONMENTAL SCIENCES↗

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↗

Role of CO 2 , climate and land use in regulating the seasonal amplitude increase of carbon fluxes in terrestrial ecosystems: A multimodel analysis

We examined the net terrestrial carbon flux to the atmosphere (F TA ) simulated by nine models from the TRENDY dynamic global vegetation model project for its seasonal cycle and amplitude trend during 1961-2012. While some models exhibit similar phase and amplitude compared to atmospheric inversions, with spring drawdown and autumn rebound, others tend to rebound early in summer. The model ensemble mean underestimates the magnitude of the seasonal cycle by 40g% compared to atmospheric inversions. Global F TA amplitude increase (19 ± 8%) and its decadal variability from the model ensemble are generally consistent with constraints from surface atmosphere observations. However, models disagree on attribution of this long-term amplitude increase, with factorial experiments attributing 83 ± 56%, -3 ± 74 and 20 ± 30% to rising CO 2 , climate change and land use/cover change, respectively. Seven out of the nine models suggest that CO 2 fertilization is the strongest control -with the notable exception of VEGAS, which attributes approximately equally to the three factors. Generally, all models display an enhanced seasonality over the boreal region in response to high-latitude warming, but a negative climate contribution from part of the Northern Hemisphere temperate region, and the net result is a divergence over climate change effect. Six of the nine models show that land use/cover change amplifies the seasonal cycle of global < i > F TA : some are due to forest regrowth, while others are caused by crop expansion or agricultural intensification, as revealed by their divergent spatial patterns. We also discovered a moderate cross-model correlation between < i > F TA amplitude increase and increase in land carbon sink ( < i > R 2 Combining double low line 0.61). Our results suggest that models can show similar results in some benchmarks with different underlying mechanisms; therefore, the spatial traits of CO 2 fertilization, climate change and land use/cover changes are crucial in determining the right mechanisms in seasonal carbon cycle change as well as mean sink change.

54 ENVIRONMENTAL SCIENCES↗

MACv2-SP: a parameterization of anthropogenic aerosol optical properties and an associated Twomey effect for use in CMIP6

A simple plume implementation of the second version (v2) of the Max Planck Institute Aerosol Climatology, MACv2-SP, is described. MACv2-SP provides a prescription of anthropogenic aerosol optical properties and an associated Twomey effect. It was created to provide a harmonized description of post-1850 anthropogenic aerosol radiative forcing for climate modeling studies. MACv2-SP has been designed to be easy to implement, change and use, and thereby enable studies exploring the climatic effects of different patterns of aerosol radiative forcing, including a Twomey effect. MACv2-SP is formulated in terms of nine spatial plumes associated with different major anthropogenic source regions. The shape of the plumes is fit to the Max Planck Institute Aerosol Climatology, version 2, whose present-day (2005) distribution is anchored by surface-based observations. Two types of plumes are considered: one predominantly associated with biomass burning, the other with industrial emissions. These differ in the prescription of their annual cycle and in their optical properties, thereby implicitly accounting for different contributions of absorbing aerosol to the different plumes. A Twomey effect for each plume is prescribed as a change in the host model's background cloud-droplet population density using relationships derived from satellite data. Year-to-year variations in the amplitude of the plumes over the historical period (1850–2016) are derived by scaling the plumes with associated national emission sources of SO 2 and NH 3 . Experiments using MACv2-SP are performed with the Max Planck Institute Earth System Model. The globally and annually averaged instantaneous and effective aerosol radiative forcings are estimated to be -0.6 and -0.5 W m -2 , respectively. Forcing from aerosol–cloud interactions (the Twomey effect) offsets the reduction of clear-sky forcing by clouds, so that the net effect of clouds on the aerosol forcing is small; hence, the clear-sky forcing, which is more readily measurable, provides a good estimate of the total aerosol forcing.

Stevens, Bjorn↗

Turbulent kinetic energy over large offshore wind farms observed and simulated by the mesoscale model WRF (3.8.1)

Abstract. Wind farms affect local weather and microclimates;hence, parameterizations of their effects have been developed for numerical weather prediction models.While most wind farm parameterizations (WFPs) include drag effects of wind farms, models differ on whether or not an additionalturbulent kinetic energy (TKE) source should be included in theseparameterizations to simulate the impact of wind farms on the boundary layer.Therefore, we use aircraft measurements above large offshore wind farms in stable conditions to evaluateWFP choices. Of the three case studies we examine, we find the simulated ambient backgroundflow to agree with observations of temperature stratification and winds. This agreement allows us toexplore the sensitivity of simulated wind farm effects with respect to modeling choicessuch as whether or not to include a TKE source, horizontal resolution, vertical resolutionand advection of TKE. For a stably stratified marine atmospheric boundary layer (MABL), a TKE source and a horizontal resolutionon the order of 5 km or finer are necessary to represent the impact of offshore wind farms on the MABL.Additionally, TKE advection results in excessively reduced TKE over the wind farms, which in turn causesan underestimation of the wind speed deficit above the wind farm. Furthermore, using fine verticalresolution increases the agreement of the simulated wind speed with satellite observations of surface wind speed.

17 WIND ENERGY↗

Deep-Learning-derived Boundary Layer Height from Meteorological Data over the SGP, GOAMAZON, CACTI

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, designed to estimate PBLH by integrating morning temperature profiles with surface meteorological observations. The DNN model is developed by leveraging a rich data set of PBLH derived from long-standing radiosonde records and augmented with high-resolution micropulse 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 data set 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 micropulse 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 (tropical rainforest) and CACTI (middle-latitude mountain) campaigns. These findings demonstrate the effectiveness of deep learning models in estimating PBLH, enhancing our understanding of boundary-layer dynamics with implications for enhancing the representation of PBL in weather forecasting and climate modeling.

54 ENVIRONMENTAL SCIENCES↗

Deformed waveshape of quantum oscillation in magnetocaloric effect for layered organic superconductor.

Magnetocaloric effect for a layered organic superconductor beta ''-(BEDT-TTF)(2)SF5CH2CF2SO3 has been investigated. At low magnetic fields, a sinusoidal quantum oscillation, arising from a closed Fermi surface, is observed. As the field increases, the waveshape of the oscillation is strongly deformed and then sharp peaks emerge. The total energy including the Landau quantized states and the elastic energy of the leads holding the sample is calculated as a function of field strength and angle, and the minimum total energy, which determines the sample angle, is obtained as a function of field. The calculated results clarify that the deformation of the quantum oscillation is ascribed to a tilting effect of the sample by the magnetic torque.

Sugiura, Shiori↗