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DOE OSTI2017

The Formation and Physical Origin of Highly Ionized Cooling Gas

We present a simple model that explains the origin of warm, diffuse gas seen primarily as highly ionized absorption-line systems in the spectra of background sources. We predict the observed column densities of several highly ionized transitions such as O vi, O vii, Ne viii, N v, and Mg x, and we present a unified comparison of the model predictions with absorption lines seen in the Milky Way disk, Milky Way halo, starburst galaxies, the circumgalactic medium, and the intergalactic medium at low and high redshifts. We show that diffuse gas seen in such diverse environments can be simultaneously explained by a simple model of radiatively cooling gas. We show that most such absorption-line systems are consistent with being collisionally ionized, and we estimate the maximum-likelihood temperature of the gas in each observation. This model satisfactorily explains why O vi is regularly observed around star-forming low- z L* galaxies, and why N v is rarely seen around the same galaxies. We further present some consequences of this model in quantifying the dynamics of the cooling gas around galaxies and predict the shock velocities associated with such flows. A unique strength of this model is that while it has only one free (but physically well-constrained) parameter, it nevertheless successfully reproduces the available data on O vi absorbers in the interstellar, circumgalactic, intragroup, and intergalactic media, as well as the available data on other absorption lines from highly ionized species.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

It’s Dust: Solving the Mysteries of the Intrinsic Scatter and Host-galaxy Dependence of Standardized Type Ia Supernova Brightnesses

The use of Type Ia supernovae (SNe Ia) as cosmological tools has motivated significant effort to understand what drives the intrinsic scatter of SN Ia distance modulus residuals after standardization, characterize the distribution of SN Ia colors, and explain why properties of the host galaxies of the SNe correlate with SN Ia distance modulus residuals. We use a compiled sample of ~1450 spectroscopically confirmed photometric light curves of SNe Ia and propose a solution to these three problems simultaneously that also explains an empirical 11 σ detection of the dependence of Hubble residual scatter on SN Ia color. We introduce a physical model of color where intrinsic SN Ia colors with a relatively weak correlation with luminosity are combined with extrinsic dust-like colors ( E ( B - V )) with a wide range of extinction parameter values ( R V ). This model captures the observed trends of Hubble residual scatter and indicates that the dominant component of SN Ia intrinsic scatter is variation in R V . We also find that the recovered E ( B - V ) and R V distributions differ based on global host-galaxy stellar mass, and this explains the observed correlation ( γ ) between mass and Hubble residuals seen in past analyses, as well as an observed 4.5 σ dependence of γ on SN Ia color. This finding removes any need to ascribe different intrinsic luminosities to different progenitor systems. Finally, we measure biases in the equation of state of dark energy ( w ) up to |Δ w | = 0.04 by replacing previous models of SN color with our dust-based model; this bias is larger than any systematic uncertainty in previous SN Ia cosmological analyses.

Astronomy & Astrophysics↗

DOE OSTI2023

The Early Light Curve of the Type Ia Supernova 2021hpr in NGC 3147: Progenitor Constraints with the Companion Interaction Model

The progenitor system of Type Ia supernovae (SNe Ia) is expected to be a close binary system consisting of a carbon/oxygen white dwarf (WD) and a nondegenerate star or another WD. Here, we present results from high-cadence monitoring observations of SN 2021hpr in a spiral galaxy, NGC 3147, and constraints on the progenitor system based on its early multicolor light-curve data. First, we classify SN 2021hpr as a normal SN Ia from its long-term photometric and spectroscopic data. More interestingly, we found a significant "early excess" in the light curve over a simple power-law ~t 2 evolution. The early light curve evolves from blue to red to blue during the first week. To explain this, we fitted the early part of the BVRI-band light curves with a two-component model consisting of ejecta–companion interaction and a simple power-law model. The early excess and its color can be explained by shock-cooling emission due to a companion star having a radius of 8.84 ± 0.58 R ⊙ . We also examined Hubble Space Telescope preexplosion images, finding no detection of a progenitor candidate, consistent with the above result. However, we could not detect signs of a significant amount of stripped mass from a nondegenerate companion star (≲0.003 M ⊙ for Hα emission). The early excess light in the multiband light curve supports a nondegenerate companion in the progenitor system of SN 2021hpr. At the same time, the nondetection of emission lines opens the door for other methods to explain this event.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

FIRST OBSERVATIONAL SIGNATURE OF ROTATIONAL DECELERATION IN A MASSIVE, INTERMEDIATE-AGE STAR CLUSTER IN THE MAGELLANIC CLOUDS

While the extended main-sequence turnoffs (eMSTOs) found in almost all 1–2 Gyr old star clusters in the Magellanic Clouds are often explained by postulating extended star formation histories (SFHs), the tight subgiant branches (SGBs) seen in some clusters challenge this popular scenario. Puzzlingly, the SGB of the eMSTO cluster NGC 419 is significantly broader at bluer than at redder colors. We carefully assess and confirm the reality of this observational trend. If we would assume that the widths of the features in color–magnitude space were entirely owing to a range in stellar ages, the SFHs of the eMSTO stars and the blue SGB region would be significantly more prolonged than that of the red part of the SGB. This cannot be explained by assuming an internal age spread. We show that rotational deceleration of a population of rapidly rotating stars, a currently hotly debated alternative scenario, naturally explains the observed trend along the SGB. Our analysis shows that a “converging” SGB could be produced if the cluster is mostly composed of rapidly rotating stars that slow down over time owing to the conservation of angular momentum during their evolutionary expansion from main-sequence turnoff stars to red giants.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

The Fuzzball Paradigm

We describe the puzzles that arise in the quantum theory of black holes, and explain how they are resolved in string theory. We review how the Bekenstein entropy is obtained through the count of brane bound states. We describe the fuzzball construction of black hole microstates. These states have no horizon and radiate from their surface like a normal body, so there is no information puzzle. We explain how the semiclassical approximation is violated in gravitational collapse even though curvatures are low at the classical horizon. This violation happens because the collapse leads to a stretching of space that is {\it fast}: light does not have time to travel across the collapsing region to establish the `vecro' correlations needed in the quantum gravitational vacuum. These vecro correlations arise from the existence of virtual fuzzball fluctuations in the gravitational vacuum, and are significant because of the large degeneracy of fuzzball states implied by the Bekenstein entropy. It is plausible that similar effects of fast expansion may be responsible for effects like dark energy and the Early Dark Energy postulated to explain the Hubble tension.

FOS: Physical sciences↗

DOE OSTI2016

In situ secondary organic aerosol formation from ambient pine forest air using an oxidation flow reactor

Abstract. An oxidation flow reactor (OFR) is a vessel inside which the concentration of a chosen oxidant can be increased for the purpose of studying SOA formation and aging by that oxidant. During the BEACHON-RoMBAS (Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics & Nitrogen–Rocky Mountain Biogenic Aerosol Study) field campaign, ambient pine forest air was oxidized by OH radicals in an OFR to measure the amount of SOA that could be formed from the real mix of ambient SOA precursor gases, and how that amount changed with time as precursors changed. High OH concentrations and short residence times allowed for semicontinuous cycling through a large range of OH exposures ranging from hours to weeks of equivalent (eq.) atmospheric aging. A simple model is derived and used to account for the relative timescales of condensation of low-volatility organic compounds (LVOCs) onto particles; condensational loss to the walls; and further reaction to produce volatile, non-condensing fragmentation products. More SOA production was observed in the OFR at nighttime (average 3 µg m−3 when LVOC fate corrected) compared to daytime (average 0.9 µg m−3 when LVOC fate corrected), with maximum formation observed at 0.4–1.5 eq. days of photochemical aging. SOA formation followed a similar diurnal pattern to monoterpenes, sesquiterpenes, and toluene+p-cymene concentrations, including a substantial increase just after sunrise at 07:00 local time. Higher photochemical aging (> 10 eq. days) led to a decrease in new SOA formation and a loss of preexisting OA due to heterogeneous oxidation followed by fragmentation and volatilization. When comparing two different commonly used methods of OH production in OFRs (OFR185 and OFR254-70), similar amounts of SOA formation were observed. We recommend the OFR185 mode for future forest studies. Concurrent gas-phase measurements of air after OH oxidation illustrate the decay of primary VOCs, production of small oxidized organic compounds, and net production at lower ages followed by net consumption of terpenoid oxidation products as photochemical age increased. New particle formation was observed in the reactor after oxidation, especially during times when precursor gas concentrations and SOA formation were largest. Approximately 4.4 times more SOA was formed in the reactor from OH oxidation than could be explained by the VOCs measured in ambient air. To our knowledge this is the first time that this has been shown when comparing VOC concentrations with SOA formation measured at the same time, rather than comparing measurements made at different times. Several recently developed instruments have quantified ambient semivolatile and intermediate-volatility organic compounds (S/IVOCs) that were not detected by a proton transfer reaction time-of-flight mass spectrometer (PTR-TOF-MS). An SOA yield of 18–58 % from those compounds can explain the observed SOA formation. S/IVOCs were the only pool of gas-phase carbon that was large enough to explain the observed SOA formation. This work suggests that these typically unmeasured gases play a substantial role in ambient SOA formation. Our results allow ruling out condensation sticking coefficients much lower than 1. These measurements help clarify the magnitude of potential SOA formation from OH oxidation in forested environments and demonstrate methods for interpretation of ambient OFR measurements.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

System wide analyses have underestimated protein abundances and the importance of transcription in mammals

Large scale surveys in mammalian tissue culture cells suggest that the protein expressed at the median abundance is present at 8000–16 000 molecules per cell and that differences in mRNA expression between genes explain only 10–40% of the differences in protein levels. We find, however, that these surveys have significantly underestimated protein abundances and the relative importance of transcription. Using individual measurements for 61 housekeeping proteins to rescale whole proteome data from Schwanhausser et al. (2011), we find that the median protein detected is expressed at 170 000 molecules per cell and that our corrected protein abundance estimates show a higher correlation with mRNA abundances than do the uncorrected protein data. In addition, we estimated the impact of further errors in mRNA and protein abundances using direct experimental measurements of these errors. The resulting analysis suggests that mRNA levels explain at least 56% of the differences in protein abundance for the 4212 genes detected by Schwanhausser et al. (2011), though because one major source of error could not be estimated the true percent contribution should be higher. We also employed a second, independent strategy to determine the contribution of mRNA levels to protein expression. We show that the variance in translation rates directly measured by ribosome profiling is only 12% of that inferred by Schwanhausser et al. (2011), and that the measured and inferred translation rates correlate poorly (R2 = 0.13). Based on this, our second strategy suggests that mRNA levels explain ~81% of the variance in protein levels. We also determined the percent contributions of transcription, RNA degradation, translation and protein degradation to the variance in protein abundances using both of our strategies. While the magnitudes of the two estimates vary, they both suggest that transcription plays a more important role than the earlier studies implied and translation a much smaller role. Finally, the above estimates only apply to those genes whose mRNA and protein expression was detected. Based on a detailed analysis by Hebenstreit et al. (2012), we estimate that approximately 40% of genes in a given cell within a population express no mRNA. Since there can be no translation in the absence of mRNA, we argue that differences in translation rates can play no role in determining the expression levels for the ~40% of genes that are non-expressed.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2012

Open-Source GIS

The components making up an Open Source GIS are explained in this chapter. A map server (Sect. 30.1) can broadly be defined as a software platform for dynamically generating spatially referenced digital map products. The University of Minnesota MapServer (UMN Map Server) is one such system. Its basic features are visualization, overlay, and query. Section 30.2 names and explains many of the geospatial open source libraries, such as GDAL and OGR. The other libraries are FDO, JTS, GEOS, JCS, MetaCRS, and GPSBabel. The application examples include derived GIS-software and data format conversions. Quantum GIS, its origin and its applications explained in detail in Sect. 30.3. The features include a rich GUI, attribute tables, vector symbols, labeling, editing functions, projections, georeferencing, GPS support, analysis, and Web Map Server functionality. Future developments will address mobile applications, 3-D, and multithreading. The origins of PostgreSQL are outlined and PostGIS discussed in detail in Sect. 30.4. It extends PostgreSQL by implementing the Simple Feature standard. Section 30.5 details the most important open source licenses such as the GPL, the LGPL, the MIT License, and the BSD License, as well as the role of the Creative Commons.

Vatsavai, Raju↗

DOE OSTI2013

Seminar 14 - Desiccant Enhanced Air Conditioning: Desiccant Enhanced Evaporative Air Conditioning (Presentation)

This presentation explains how liquid desiccant based coupled with an indirect evaporative cooler can efficiently produce cool, dry air, and how a liquid desiccant membrane air conditioner can efficiently provide cooling and dehumidification without the carryover problems of previous generations of liquid desiccant systems. It provides an overview to a liquid desiccant DX air conditioner that can efficiently provide cooling and dehumidification to high latent loads without the need for reheat, explains how liquid desiccant cooling and dehumidification systems can outperform vapor compression based air conditioning systems in hot and humid climates, explains how liquid desiccant cooling and dehumidification systems work, and describes a refrigerant free liquid desiccant based cooling system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Critical Infrastructure Classification via CNN-based Modeling and Image Analysis

With recent advances in the fields of satellite imagery and machine learning we now have the ability to develop explainable deep learning models that enhance critical infrastructure analysis. Funded through Idaho National Laboratory’s (INL) Laboratory Directed Research and Development (LDRD) office we are in the process of developing a deep learning model capable of identifying critical infrastructure facilities and embedded features within those facilities. Utilizing current limit of practice techniques in the machine learning areas of explainability and transfer learning our model, once complete, will have the capacity to be used on multiple different imagery data sets and produce results that not only classify critical infrastructure facilities, but also explain why a critical infrastructure facility was classified as a certain type of facility. These advancements eliminate the ‘black box’ approach deep learning models have had in the past, where a user will have to trust the conclusion of a model without understanding what reasoning when into the model’s classification process. They also expand a model’s usefulness, traditionally a deep learning model will have to use the same data set it was originally trained on. Given the long training times of deep learning models this is impractical in a number of scenarios. By utilizing transfer learning advancements, we are eliminating the need to train our model on the same data set it is then run on to classify critical infrastructure facilities. We are also enabling the analysis and classification of data sets that are potentially too small to be divided into a training and testing data set. Once completed this model can provide a foundation to enhanced critical infrastructure analysis, dependency analysis, and potential disaster relief efforts.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2011

Validation and Simplification of the Radiation Therapy Oncology Group Recursive Partitioning Analysis Classification for Glioblastoma

Purpose: Previous recursive partitioning analysis (RPA) of patients with malignant glioma (glioblastoma multiforme [GBM] and anaplastic astrocytoma [AA]) produced six prognostic groups (I-VI) classified by six factors. We sought here to determine whether the classification for GBM could be improved by using an updated Radiation Therapy Oncology Group (RTOG) GBM database excluding AA and by considering additional baseline variables. Methods and Materials: The new analysis considered 42 baseline variables and 1,672 GBM patients from the expanded RTOG glioma database. Patients receiving radiation only were excluded such that all patients received radiation+carmustine. 'Radiation dose received' was replaced with 'radiation dose assigned.' The new RPA models were compared with the original model by applying them to a test dataset comprising 488 patients from six other RTOG trials. Fitness of the original and new models was evaluated using explained variation. Results: The original RPA model explained more variations in survival in the test dataset than did the new models (20% vs. 15%) and was therefore chosen for further analysis. It was reduced by combining Classes V and VI to produce three prognostic classes (Classes III, IV, and V+VI), as Classes V and VI had indistinguishable survival in the test dataset. The simplified model did not further improve performance (explained variation 18% vs. 20%) but is easier to apply because it involves only four variables: age, performance status, extent of resection, and neurologic function. Applying this simplified model to the updated GBM database resulted in three distinct classes with median survival times of 17.1, 11.2, and 7.5 months for Classes III, IV, and V+VI, respectively. Conclusions: The final model, the simplified original RPA model combining Classes V and VI, resulted in three distinct prognostic groups defined by age, performance status, extent of resection, and neurologic function. This classification will be used in future RTOG GBM trials.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2023

A Real-Time ANPC Inverter Digital Twin with Integrated Design-For-Trust

The demand for renewable energy has increased over the last few years, and so has the demand for greater expectations within the energy market. This increasing trend has been accompanied by more significant usage of internet-connected devices (IoT), leading to critical electrical infrastructure being connected to the internet. Implementing internet connectivity with such devices and systems provides benefits such as improving the system's performance, facilitating irregularity and anomaly mitigation, and providing additional situational awareness for enhanced decision-making. However, enhancing the connected system with IoT introduces a drawback – a greater vulnerability to cyber-attacks. Cyber-attacks targeting critical infrastructure in the electrical sector have occurred in the United States and Ukraine. These cyber-attacks highlight and expose vulnerabilities that a system inherits when connecting to the internet. These attacks left thousands of customers without electricity for hours until operators could regain control of the electric utility grid. Therefore, to address the vulnerabilities of an internet-connected power electronic device, this work focused on the hardware layer of the system. Implementing a cyber-control system inside the hardware layer can significantly reduce the possibility of an attacker patching malicious controller firmware into a photovoltaic grid-connected inverter, thus mitigating the likelihood that the inverter becomes inactive a cyber-attack scenario. With this mitigation technique, if a cyberattack is successful and an attacker gains control of the network, a cyber-defense technique is in place to mitigate the impact of the cyber-attack. This additional protection layer was developed based on an innovative concept known as Digital Twin (DT). A DT, in this case, replicates an Active-Neutral Point Clamped (ANPC) inverter and was designed using a hardware language known as VHDL (Very High-Speed Integrated Circuit Hardware Description Language) and applied to Field-Programmable-GateArray (FPGA). The DT is embedded within the FPGA and contained in a controller board, the UCB (Unified Controller Board), developed by the University of Arkansas electrical engineering team. This UCB also contains two Digital Signal Processors (DSPs) responsible for generating associated signals to control an authentic physical inverter. These DSP signals are received and processed by the FPGA that implements the DT of an ANPC; in other words, it simulates in realtime the expected output of an actual ANPC inverter using the signals from the DSP. When a new firmware is ready to be patched, the DT provides output signals simulating behavior that a real ANPC inverter would generate with the new firmware. The new firmware is tested to check if it meets all the operational requirements established using a Design-For-Trust technique (DFTr). If the new firmware fails in at least one of the DFT tests, it is considered malicious and must be rejected. This work is divided into sections, such as Background, which explains the pieces that were used and the strategy behind this work; Process and Procedure, which explains the methodology that was adopted to prove the reliability and effectiveness of this work; Results and Discussion, where the simulations and results are described and explained; followed by Conclusion and Future work section, which concludes this work and adds possible future projects to continue this work further.

do Amaral Custodio, Paulo Vitor↗

DOE OSTI2023

A detailed study of interpretability of deep neural network based top taggers

Abstract Recent developments in the methods of explainable artificial intelligence (XAI) allow researchers to explore the inner workings of deep neural networks (DNNs), revealing crucial information about input–output relationships and realizing how data connects with machine learning models. In this paper we explore interpretability of DNN models designed to identify jets coming from top quark decay in high energy proton–proton collisions at the Large Hadron Collider. We review a subset of existing top tagger models and explore different quantitative methods to identify which features play the most important roles in identifying the top jets. We also investigate how and why feature importance varies across different XAI metrics, how correlations among features impact their explainability, and how latent space representations encode information as well as correlate with physically meaningful quantities. Our studies uncover some major pitfalls of existing XAI methods and illustrate how they can be overcome to obtain consistent and meaningful interpretation of these models. We additionally illustrate the activity of hidden layers as neural activation pattern diagrams and demonstrate how they can be used to understand how DNNs relay information across the layers and how this understanding can help to make such models significantly simpler by allowing effective model reoptimization and hyperparameter tuning. These studies not only facilitate a methodological approach to interpreting models but also unveil new insights about what these models learn. Incorporating these observations into augmented model design, we propose the particle flow interaction network model and demonstrate how interpretability-inspired model augmentation can improve top tagging performance.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

The Primary and Recycling Sources of OH During the NACHTT-2011 Campaign: HONO as an Important OH Primary Source in the Wintertime

We present OH observation results during the NACHTT-11 field campaign at the Boulder Atmospheric Observatory in Weld County, Colorado. The observed OH levels during the daytime (at noon) were ~ 2.7 × 106 molecules cm-3 at the ground level (2 m above ground level, AGL). HONO and ozone photolysis were the two dominant photochemical OH production pathways during the field campaign. However, alkene ozonolysis, found an important source for OH by two previous winter season OH observations, was a minor contribution to OH primary production (~5 %). To evaluate recycling sources of OH from HO2 and RO2, an observation constrained University of Washington Chemical Mechanism (UWCM) box model is employed to simulated ambient OH levels with different model scenarios. For the base run without constraining observed HONO, the model simulated OH significantly underestimates the observed OH level (20.8 times in the morning and 7.2 times in the daytime). This indicates that the known HONO sources incorporated in the UWCM model cannot explain the observed HONO level. Once HONO is constrained by the observation, the discrepancy between observation and model simulation improves (5.1 times in the morning and 2.1 times in the daytime) but still out of the measurement uncertainty range (35 %). We explore two possible reasons for the observed unexplainably high wintertime OH levels. First, potential roles of Cl atoms produce organic peroxy radicals from the reactions between Cl atmos and alkane compounds. However, the Cl levels during the observation period are estimated very low (~ 103 atoms cm-3) to explain the enhanced OH levels. Second, Impacts of higher HONO levels on the ground was evaluated. Strong HONO gradient towards ground was observed especially during the early morning (6 am to 8 am) was observed and the lowest level available for the HONO observation during the campaign is 5 m AGL. Once we assume the twice of the observed HONO levels averaged between 5 m to 15 m at 2 m AGL, model predicted OH levels agree well within the observation uncertainty range. Wintertime photochemistry has not been investigated as much as the summer season. The results of this study along with a limited number of winter OH observations clearly urge further investigation on tropospheric oxidation capacity in the winter season considering implications of tropospheric oxidation capacity to the short-lived climate forcers especially methane.

Kim, S.↗

DOE OSTI2014

Impact of large-scale dynamics on the microphysical properties of midlatitude cirrus

In situ microphysical observations 3 of mid-latitude cirrus collected during the Department of Energy Small Particles in Cirrus (SPAR-TICUS) field campaign are combined with an atmospheric state classification for the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site to understand statistical relationships between cirrus microphysics and the large-scale meteorology. The atmospheric state classification is informed about the large-scale meteorology and state of cloudiness at the ARM SGP site by combining ECMWF ERA-Interim reanalysis data with 14 years of continuous observations from the millimeter-wavelength cloud radar. Almost half of the cirrus cloud occurrences in the vicinity of the ARM SGP site during SPARTICUS can be explained by three distinct synoptic condi- tions, namely upper-level ridges, mid-latitude cyclones with frontal systems and subtropical flows. Probability density functions (PDFs) of cirrus micro- physical properties such as particle size distributions (PSDs), ice number con- centrations and ice water content (IWC) are examined and exhibit striking differences among the different synoptic regimes. Generally, narrower PSDs with lower IWC but higher ice number concentrations are found in cirrus sam- pled in upper-level ridges whereas cirrus sampled in subtropical flows, fronts and aged anvils show broader PSDs with considerably lower ice number con- centrations but higher IWC. Despite striking contrasts in the cirrus micro- physics for different large-scale environments, the PDFs of vertical velocity are not different, suggesting that vertical velocity PDFs are a poor predic-tor for explaining the microphysical variability in cirrus. Instead, cirrus mi- crophysical contrasts may be driven by differences in ice supersaturations or aerosols.

Muhlbauer, Andreas↗

DOE OSTI2014

Evaluation of Cloud-resolving and Limited Area Model Intercomparison Simulations using TWP-ICE Observations. Part 1: Deep Convective Updraft Properties

Ten 3D cloud-resolving model (CRM) simulations and four 3D limited area model (LAM) simulations of an intense mesoscale convective system observed on January 23-24, 2006 during the Tropical Warm Pool – International Cloud Experiment (TWP-ICE) are compared with each other and with observed radar reflectivity fields and dual-Doppler retrievals of vertical wind speeds in an attempt to explain published results showing a high bias in simulated convective radar reflectivity aloft. This high bias results from ice water content being large, which is a product of large, strong convective updrafts, although hydrometeor size distribution assumptions modulate the size of this bias. Snow reflectivity can exceed 40 dBZ in a two-moment scheme when a constant bulk density of 100 kg m-3 is used. Making snow mass more realistically proportional to area rather than volume should somewhat alleviate this problem. Graupel, unlike snow, produces high biased reflectivity in all simulations. This is associated with large amounts of liquid water above the freezing level in updraft cores. Peak vertical velocities in deep convective updrafts are greater than dual-Doppler retrieved values, especially in the upper troposphere. Freezing of large rainwater contents lofted above the freezing level in simulated updraft cores greatly contributes to these excessive upper tropospheric vertical velocities. Strong simulated updraft cores are nearly undiluted, with some showing supercell characteristics. Decreasing horizontal grid spacing from 900 meters to 100 meters weakens strong updrafts, but not enough to match observational retrievals. Therefore, overly intense simulated updrafts may partly be a product of interactions between convective dynamics, parameterized microphysics, and large-scale environmental biases that promote different convective modes and strengths than observed.

clould-resolving↗

DOE OSTI2014

Evaluation of Cloud-resolving and Limited Area Model Intercomparison Simulations using TWP-ICE Observations. Part 2: Rain Microphysics

Ten 3D cloud-resolving model (CRM) simulations and four 3D limited area model (LAM) simulations of an intense mesoscale convective system observed on January 23-24, 2006 during the Tropical Warm Pool – International Cloud Experiment (TWP-ICE) are compared with each other and with observations and retrievals from a scanning polarimetric radar, co-located UHF and VHF vertical profilers, and a Joss-Waldvogel disdrometer in an attempt to explain published results showing a low bias in simulated stratiform rainfall. Despite different forcing methodologies, similar precipitation microphysics errors appear in CRMs and LAMs with differences that depend on the details of the bulk microphysics scheme used. One-moment schemes produce too many small raindrops, which biases Doppler velocities low, but produces rain water contents (RWCs) that are similar to observed. Two-moment rain schemes with a gamma shape parameter (μ) of 0 produce excessive size sorting, which leads to larger Doppler velocities than those produced in one-moment schemes, but lower RWCs than observed. Two moment schemes also produce a convective median volume diameter distribution that is too broad relative to observations and thus, may have issues balancing raindrop formation, collision coalescence, and raindrop breakup. Assuming a μ of 2.5 rather than 0 for the raindrop size distribution improves one-moment scheme biases, and allowing μ to have values greater than 0 may improve two-moment schemes. Under-predicted stratiform rain rates are associated with under-predicted ice water contents at the melting level rather than excessive rain evaporation, in turn likely associated with convective detrainment that is too high in the troposphere and mesoscale circulations that are too weak. In addition to stronger convective updrafts than observed, limited domain size prevents a large, well-developed stratiform region from developing in CRMs, while a dry bias in ECMWF analyses does the same to the LAMs.

cloud-resolving↗

DOE OSTI2015

Global patterns and controls of soil organic carbon dynamics as simulated by multiple terrestrial biosphere models. Current status and future directions

Soil is the largest organic carbon (C) pool of terrestrial ecosystems, and loss from soil accounts for a large pro portion of land-atmosphere C exchange. Due to large pool size and variable residence time from years to millennia, even small changes in soil organic C(SOC) have substantial effects on the terrestrial C budget, thereby affecting atmospheric carbon dioxide (CO2)concentration and climate change. In the past decades, a wide variety of studies have been conducted to quantify global SOC stocks and soil exchange with the atmosphere through site measurements, inventories, and empirical/process-based modeling. However, these estimates are highly uncertain and identifying major driving forces controlling soil C storage and fluxes remains a key research challenge his study has compiled century-long (1901-2010)estimates of SOC storage and heterotrophic respiration (Rh) from ten terrestrial biosphere models (TBMs) in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) and two observation based datasets. The ten-TBM ensemble shows that global SOC estimate range from 4 to 2111 Pg C (1 Pg = 10 15 g) with a median value of 1158 Pg C33 in 2010. Modeling approach estimates a broad range of Rh from 35 to 69 Pg C yr -1 with a median value of 51Pg C yr -1 during 200–2010. The largest uncertainty in SOC stocks exists in the 40–65°N latitude band while Rh differences are the largest in the tropics. All the models agreed that climate and land use changes have decreased SOC stocks while elevated CO 2 and atmospheric nitrogen deposition have increased SOC stocks though the response varied significantly among models. Model representations of temperature and moisture sensitivity,nutrient limitation and land use partially explain the divergent estimates of global SOC stocks and soil fluxes in this study. In addition, major sources of uncertainty from model estimation include exclusion of SOC storage in wetlands and peatlands as well as C storage in deep soil layers.

54 ENVIRONMENTAL SCIENCES↗