Beyond the Thickness Distribution: Modeling and Evaluating Sea Ice Thickness in Earth System Models
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Modeling Systems of Interacting Specialists Presentation to Savannah River modeling team.
Abstract not provided.
Beyeler, Walter E↗
Collaborative Project. Mode and Intermediate Waters in Earth System Models
The focus of this grant was on diagnosing the physical mechanisms controlling upper ocean water mass formation and carbon distribution in Earth System Models (ESMs), with the goal of improving the physics that controls their formation.
59 BASIC BIOLOGICAL SCIENCES↗
Earth System Model Parameter Adjustment Using a Green's Functions Approach
We demonstrate the practicality and effectiveness of using a Green's functions estimation approach for adjusting uncertain parameters in an Earth system model (ESM). This estimation approach has previously been applied to an intermediate-complexity climate model and to individual ESM components, e.g., ocean, sea ice, or carbon cycle components. Here, the Green's functions approach is applied to a state-of-the-art ESM that comprises a global atmosphere/land configuration of the Goddard Earth Observing System (GEOS) coupled to an ocean and sea ice configuration of the Massachusetts Institute of Technology general circulation model (MITgcm). Horizontal grid spacing is approximately 110 km for GEOS and 37–110 km for MITgcm. In addition to the reference GEOS-MITgcm simulation, we carried out a series of model sensitivity experiments, in which 20 uncertain parameters are perturbed. These “control” parameters can be used to adjust sea ice, microphysics, turbulence, radiation, and surface schemes in the coupled simulation. We defined eight observational targets: sea ice fraction, net surface shortwave radiation, downward longwave radiation, near-surface temperature, sea surface temperature, sea surface salinity, and ocean temperature and salinity at 300 m. We applied the Green's functions approach to optimize the values of the 20 control parameters so as to minimize a weighted least-squares distance between the model and the eight observational targets. The new experiment with the optimized parameters resulted in a total cost reduction of 9 % relative to a simulation that had already been adjusted using other methods. The optimized experiment attained a balanced cost reduction over most of the observational targets. We also report on results from a set of sensitivity experiments that are not used in the final optimized simulation but helped explore options and guided the optimization process. These experiments include an assessment of sensitivity to the number of control parameters and to the selection of observational targets and weights in the cost function. Based on these sensitivity experiments, we selected a specific definition for the cost function. The sensitivity experiments also revealed a decreasing overall cost as the number of control variables was increased. In summary, we recommend using the Green's functions estimation approach as an additional fine-tuning step in the model development process. The method is not a replacement for modelers' experience in choosing and adjusting sensitive model parameters. Instead, it is an additional practical and effective tool for carrying out final adjustments of uncertain ESM parameters.
Green's Function↗
SU-E-I-11: Cascaded Linear System Model for Columnar CsI Flat Panel Imagers with Depth Dependent Gain and Blur
Purpose: To implement a depth dependent gain and blur cascaded linear system model (CLSM) for optimizing columnar structured CsI indirect conversion flat panel imager (FPI) for advanced imaging applications. Methods: For experimental validation, depth dependent escape efficiency, e(z), was extracted from PHS measurement of different CsI scintillators (thickness, substrate and light output). The inherent MTF and DQE of CsI was measured using high resolution CMOS sensor. For CLSM, e(z) and the depth dependent MTF(f,z), were estimated using Monte Carlo simulation (Geant4) of optical photon transport through columnar CsI. Previous work showed that Monte Carlo simulation for CsI was hindered by the non-ideality of its columnar structure. In the present work we allowed variation in columnar width with depth, and assumed diffusive reflective backing and columns. Monte Carlo simulation was performed using an optical point source placed at different depth of the CsI layer, from which MTF(z,f) and e(z) were computed. The resulting e(z) with excellent matching with experimental measurements were then applied to the CLSM, Monte Carlo simulation was repeated until the modeled MTF, DQE(f) also match experimental measurement. Results: For a 150 micron FOS HL type CsI, e(z) varies between 0.56 to 0.45, and the MTF at 14 cycles/mm varies between 62.1% to 3.9%, from the front to the back of the scintillator. The overall MTF and DQE(f) at all frequencies are in excellent agreement with experimental measurements at all frequencies. Conclusion: We have developed a CLSM for columnar CsI scintillators with depth dependent gain and MTF, which were estimated from Monte Carlo simulation with novel optical simulation settings. Preliminary results showed excellent agreement between simulation results and experimental measurements. Future work is aimed at extending this approach to optimize CsI screen optic design and sensor structure for achieving higher DQE(f) in cone-beam CT, which uses high kVp.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Atmospheric processing of iron in mineral and combustion aerosols: development of an intermediate-complexity mechanism suitable for Earth system models
Abstract. Atmospheric processing of iron in dust and combustion aerosols is simulated using an intermediate-complexity soluble iron mechanism designed for Earth system models. The solubilization mechanism includes both a dependence on aerosol water pH and in-cloud oxalic acid. The simulations of size-resolved total, soluble and fractional iron solubility indicate that this mechanism captures many but not all of the features seen from cruise observations of labile iron. The primary objective was to determine the extent to which our solubility scheme could adequately match observations of fractional iron solubility. We define a semi-quantitative metric as the model mean at points with observations divided by the observational mean (MMO). The model is in reasonable agreement with observations of fractional iron solubility with an MMO of 0.86. Several sensitivity studies are performed to ascertain the degree of complexity needed to match observations; including the oxalic acid enhancement is necessary, while different parameterizations for calculating model oxalate concentrations are less important. The percent change in soluble iron deposition between the reference case (REF) and the simulation with acidic processing alone is 63.8 %, which is consistent with previous studies. Upon deposition to global oceans, global mean combustion iron solubility to total fractional iron solubility is 8.2 %; however, the contribution of fractional iron solubility from combustion sources to ocean basins below 15∘ S is approximately 50 %. We conclude that, in many remote ocean regions, sources of iron from combustion and dust aerosols are equally important. Our estimates of changes in deposition of soluble iron to the ocean since preindustrial climate conditions suggest roughly a doubling due to a combination of higher dust and combustion iron emissions along with more efficient atmospheric processing.
Scanza, Rachel A.↗
A Systems Model for SWS Safety Demonstrator (SD-1): Wildfire Response Operations
The aim of this project is the build out of a System Safety Model for System-Wide Safety’s Safety Demonstrator 1 (SD-1), which will be a demonstration of an In-Time Aviation Safety Management System (IASMS) in emerging wildfire response operations
model-based systems engineering↗
A new synoptic scale resolving global climate simulation using the Community Earth System Model
Abstract High‐resolution global climate modeling holds the promise of capturing planetary‐scale climate modes and small‐scale (regional and sometimes extreme) features simultaneously, including their mutual interaction. This paper discusses a new state‐of‐the‐art high‐resolution Community Earth System Model (CESM) simulation that was performed with these goals in mind. The atmospheric component was at 0.25° grid spacing, and ocean component at 0.1°. One hundred years of “present‐day” simulation were completed. Major results were that annual mean sea surface temperature (SST) in the equatorial Pacific and El‐Niño Southern Oscillation variability were well simulated compared to standard resolution models. Tropical and southern Atlantic SST also had much reduced bias compared to previous versions of the model. In addition, the high resolution of the model enabled small‐scale features of the climate system to be represented, such as air‐sea interaction over ocean frontal zones, mesoscale systems generated by the Rockies, and Tropical Cyclones. Associated single component runs and standard resolution coupled runs are used to help attribute the strengths and weaknesses of the fully coupled run. The high‐resolution run employed 23,404 cores, costing 250 thousand processor‐hours per simulated year and made about two simulated years per day on the NCAR‐Wyoming supercomputer “Yellowstone.”
Small, R. Justin↗
A Process for the Creation of T-MATS Propulsion System Models from NPSS Data
A modular thermodynamic simulation package called the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) has been developed for the creation of dynamic simulations. The T-MATS software is designed as a plug-in for Simulink(Registered TradeMark) and allows a developer to create system simulations of thermodynamic plants (such as gas turbines) and controllers in a single tool. Creation of such simulations can be accomplished by matching data from actual systems, or by matching data from steady state models and inserting appropriate dynamics, such as the rotor and actuator dynamics for an aircraft engine. This paper summarizes the process for creating T-MATS turbo-machinery simulations using data and input files obtained from a steady state model created in the Numerical Propulsion System Simulation (NPSS). The NPSS is a thermodynamic simulation environment that is commonly used for steady state gas turbine performance analysis. Completion of all the steps involved in the process results in a good match between T-MATS and NPSS at several steady state operating points. Additionally, the T-MATS model extended to run dynamically provides the possibility of simulating and evaluating closed loop responses.
gas path dynamics↗
A Process for the Creation of T-MATS Propulsion System Models from NPSS Data
A modular thermodynamic simulation package called the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) has been developed for the creation of dynamic simulations. The T-MATS software is designed as a plug-in for Simulink(Trademark) and allows a developer to create system simulations of thermodynamic plants (such as gas turbines) and controllers in a single tool. Creation of such simulations can be accomplished by matching data from actual systems, or by matching data from steady state models and inserting appropriate dynamics, such as the rotor and actuator dynamics for an aircraft engine. This paper summarizes the process for creating T-MATS turbo-machinery simulations using data and input files obtained from a steady state model created in the Numerical Propulsion System Simulation (NPSS). The NPSS is a thermodynamic simulation environment that is commonly used for steady state gas turbine performance analysis. Completion of all the steps involved in the process results in a good match between T-MATS and NPSS at several steady state operating points. Additionally, the T-MATS model extended to run dynamically provides the possibility of simulating and evaluating closed loop responses.
gas path dynamics↗
A Process for the Creation of T-MATS Propulsion System Models from NPSS data
A modular thermodynamic simulation package called the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) has been developed for the creation of dynamic simulations. The T-MATS software is designed as a plug-in for Simulink (Math Works, Inc.) and allows a developer to create system simulations of thermodynamic plants (such as gas turbines) and controllers in a single tool. Creation of such simulations can be accomplished by matching data from actual systems, or by matching data from steady state models and inserting appropriate dynamics, such as the rotor and actuator dynamics for an aircraft engine. This paper summarizes the process for creating T-MATS turbo-machinery simulations using data and input files obtained from a steady state model created in the Numerical Propulsion System Simulation (NPSS). The NPSS is a thermodynamic simulation environment that is commonly used for steady state gas turbine performance analysis. Completion of all the steps involved in the process results in a good match between T-MATS and NPSS at several steady state operating points. Additionally, the T-MATS model extended to run dynamically provides the possibility of simulating and evaluating closed loop responses.
gas path dynamics↗
EMPIRICAL VALIDATION OF MULTI-ZONE BUILDING AND HVAC SYSTEM MODELS UNDER UNCERTAINTY
This study implemented a framework of empirical validation of building energy models under uncertainty to a set of controlled experiments that aim to validate multi-zone building and HVAC system models. Energy models were created through iterative acquisitions of information and data and uses measurement data from various types of sensors as both inputs and as observations to validate predictions. Experimental and modeling uncertainties were quantified and propagated accordingly, and probabilistic accuracy metrics were used to evaluate the agreement between model predictions and observations under uncertainty. Sensitivity analysis was performed to identify the most influential uncertainties that will be prioritized to be addressed in the next steps. Current results of two cooling tests show an overall good agreement between predictions and observations on a set of HVAC system outputs despite considerable and influential uncertainty in DX cooling coil COP. Agreements on zone-level responses vary notably among individual rooms, likely because of significant uncertainties in room radiation heat gain and system supply air.
Li, Qi↗
Advanced Guide to Understanding Power System Model Results for Long-Term Resource Plans
This guide is for public utility commission staff, state energy office staff, and other stakeholders who review model results for utility integrated resource plans (IRPs). It builds on the "Beginner's Guide to Understanding Power System Model Results for Long-Term Resource Plans," and delves into more advanced topics that were not included or not fully covered in the beginner's guide. The topics included here are evolving and may or may not be important to the resource plan you are evaluating. Due to limitations in resources, it's also not possible to give the highest level of detail or attention to every topic within a plan. An important part of planning for an uncertain future involves deciding which topics deserve the most focus and resources. It's all about prioritizing efforts where they will have the most impact or be most beneficial despite uncertainties ahead. As with the beginner's guide, we intend for this guide to help improve decision-making in the electricity planning process by strengthening understanding and dialogue between electricity system planners and relevant stakeholders. The following information is designed to allow you to better engage in the planning process by evaluating results, asking questions, and thinking through what is most important. We allocate significant discussion in the guide to electricity demand evolution, demand-side resources, and resource adequacy. These topics have garnered increasing attention, hence their prominence in this guide. Other topics are also presented, but their incorporation into the planning process might vary based on interest and relevance. The absence of certain topics doesn't diminish their importance; rather, it reflects the reality that in planning, trade-offs necessitate prioritizing certain aspects over others.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Estimating Submicron Aerosol Mixing State at the Global Scale With Machine Learning and Earth System Modeling
Abstract This study integrates machine learning and particle‐resolved aerosol simulations to develop emulators that predict submicron aerosol mixing state indices from the Earth system model (ESM) simulations. The emulators predict aerosol mixing state using only quantities that are predicted by the ESM, including bulk aerosol species concentrations, which do not by themselves carry mixing state information. We used PartMC‐MOSAIC as the particle‐resolved model and NCAR's CESM as the ESM. We trained emulators for three different mixing state indices for submicron aerosol in terms of chemical species abundance ( χ a ), the mixing of optically absorbing and nonabsorbing species ( χ o ), and the mixing of hygroscopic and nonhygroscopic species ( χ h ). Our global mixing state maps show considerable spatial and seasonal variability unique to each mixing state index. Seasonal averages varied spatially between 13% and 94% for χ a , between 38% and 94% for χ o , and between 20% and 87% for χ h with global annual averages of 67%, 68%, and 56%, respectively. High values in one index can be consistent with low values in another index depending on the grouping of species and their relative abundance, meaning that each mixing state index captures different aspects of the population mixing state. Although a direct validation with observational data has not been possible yet, our results are consistent with mixing state index values derived from ambient observations. This work is a prototypical example of using machine learning emulators to add information to ESM simulations.
54 ENVIRONMENTAL SCIENCES↗
Scalable modular dynamic molten salt reactor system model with decay heat
Nodal dynamic models allow rapid reduced-order simulations of complex systems. This paper presents a publicly available system dynamic model of a molten salt reactor system with a topology of the Molten Salt Reactor Experiment (MSRE), in MATLAB/Simulink, building upon a model previously published and validated with MSRE data. It adds scaling of nominal power, dynamic representation of decay heat generation, a generic decay heat removal system, improved documentation, modularity, and test cases. One hour of system transient runs in less than 10 min on a laptop. This model is intended for first order engineering calculations, developing insights into system transient behavior, equipment sizing, parameter sensitivity studies. The model contains an easy to use toolkit which can be customized and expanded to describe any molten salt reactor system. Finally, scenarios involving off-normal transients are presented. Relation between shutdown reactivity insertions, decay heat removal, core recriticality, and safe shutdown conditions are discussed.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
2013 Community Earth System Model (CESM) Tutorial-Proposal to DOE
THE SAME REQUEST WILL BE SENT TO BOTH NSF AND DOE TO EACH SUPPORT $35K. The third annual Community Earth System Model (CESM) tutorial for students and early career scientists was held from 30 July to 3 August, 2012. This event was extremely successful and, as for the tutorials in previous years, there was a greater demand than could be met. This indicates a continuing need for a tutorial of this type and we anticipate that the 2013 tutorial will be well received. The tutorial will include lectures on simulating the climate system and practical sessions on running CESM, modifying components, and analyzing data. These will be targeted to the graduate student level. Attendance will be limited to a maximum of 80 students with financial support for up to 40 students. Attendees will be balanced across institutions.
Holland, Marika↗
The coastal streamflow flux in the Regional Arctic System Model
The coastal streamflow flux from the Arctic drainage basin is an important driver of dynamics in the coupled ice-ocean system. Comprising more than one third of the total freshwater flux into the Arctic Ocean, streamflow is a key component of the regional and global freshwater cycle. To better represent the coupling of the streamflow flux to the ocean, we have developed and applied the RVIC streamflow routing model within the Regional Arctic System Model (RASM). The RASM is a high-resolution regional Earth System Model whose domain includes all of the Arctic drainage basin. Here in this paper, we introduce the RVIC streamflow routing model, detailing its application within RASM and its advancements in terms of representing high-resolution streamflow processes. We evaluate model simulated streamflow relative to in situ observations and demonstrate a method for improving model performance using a simple optimization procedure. We also present a new, spatially and temporally consistent, high-resolution data set of coastal freshwater fluxes for the Arctic drainage basin and surrounding areas that is based on a fully coupled RASM simulation and intended for use in Arctic Ocean modeling applications. This data set is evaluated relative to other coastal streamflow data sets commonly used by the ocean modeling community. We demonstrate that the RASM-simulated streamflow flux better represents the annual cycle than existing data sets, especially in ungauged areas. Finally, we assess the impact that streamflow has on the coupled ice-ocean system, finding that the presence of streamflow leads to reduced sea surface salinity, increased sea surface temperatures, and decreased sea ice thickness.
54 ENVIRONMENTAL SCIENCES↗
Robust and Nonrobust Aspects of Atlantic Meridional Overturning Circulation Variability and Mechanisms in the Community Earth System Model
Abstract Robust and nonrobust aspects of Atlantic meridional overturning circulation (AMOC) variability and mechanisms are analyzed in several 600-yr simulations with the Community Earth System Model. The simulations consist of a set of cases where a few loosely constrained ocean model parameter values are changed, a pair of cases where round-off level perturbations are applied to the initial atmospheric temperature field, and a millennium-scale integration. The time scales of variability differ among the cases with the dominant periods ranging from decadal to centennial. These dominant periods are not stationary in time, indicating that a robust characterization of AMOC temporal variability requires long, multimillennium-scale simulations. A robust aspect is that positive anomalies of the Labrador Sea (LS) upper-ocean density and boundary layer depth and the positive phase of the North Atlantic Oscillation lead AMOC strengthening by 2–3 years. Respective contributions of temperature and salinity to these density anomalies vary across the simulations, but in a majority of the cases temperature contributions dominate. Following an AMOC intensification, all cases show that advection of warm and salty waters into the LS region results in near-neutral density anomalies. Analysis of the LS heat budget indicates that temperature acts to increase density in all cases prior to an AMOC intensification, primarily due to losses by sensible and latent heat fluxes. The accompanying salt budget analysis reveals that the salt contribution to density anomalies varies across the cases, taking both positive and negative values.
Danabasoglu, Gokhan↗