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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 523 records · Page 29
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DOE OSTI2013

Improved simulation of extreme precipitation in a high-resolution atmosphere model

Climate models often underestimate the magnitude of extreme precipitation. We compare the performance of a high-resolution (~0.25°) time-slice atmospheric simulation (1979–2005) of the Community Earth System Model 1.0 in representing daily extreme precipitation events against those of the same model at lower resolutions (~1° and 2°). We find significant increases in the simulated levels of daily extreme precipitation over Europe, the United States, and Australia. In many cases the increase in high percentiles (>95th) of daily precipitation leads to better agreement with observational data sets. For lower percentiles, we find that increasing resolution does not significantly increase values of simulated precipitation. We argue that the reduced biases mainly result from the higher resolution models resolving more key physical processes controlling heavy precipitation. Lastly, we conclude that while high resolution is vital for accurately simulating extreme precipitation, considerable biases remain at the highest available model resolutions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

The Representative Concentration Pathways: An Overview

This paper summarizes the development process and main characteristics of the Representative Concentration Pathways (RCPs), a set of four new scenarios developed for the climate modeling community as a basis for long-term and near-term modeling experiments. The four RCPs together span the range of year 2100 radiative forcing values found in the open literature, i.e. from 2.6 to 8.5 W/m2. The RCPs are the product of an innovative collaboration between integrated assessment modelers, climate modelers, terrestrial ecosystem modelers and emission inventory experts. The resulting product forms a comprehensive data set with high spatial and sectoral resolutions for the period extending to 2100. Land use and emissions of air pollutants and greenhouse gases are reported mostly at a 0.5 x 0.5 degree spatial resolution, with air pollutants also provided per sector (for well-mixed gases, a coarser resolution is used). The underlying integrated assessment model outputs for land use, atmospheric emissions and concentration data were harmonized across models and scenarios to ensure consistency with historical observations while preserving individual scenario trends. For most variables, the RCPs cover a wide range of the existing literature. The RCPs are supplemented with extensions (Extended Concentration Pathways, ECPs), which allow climate modeling experiments through the year 2300. The RCPs are an important development in climate research and provide a potential foundation for further research and assessment, including emissions mitigation and impact analysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Influence of Sea Ice on Arctic Marine Sulfur Biogeochemistry in the Community Climate System Model

Global climate models (GCMs) have not effectively considered how responses of arctic marine ecosystems to a warming climate will influence the global climate system. A key response of arctic marine ecosystems that may substantially influence energy exchange in the Arctic is a change in dimethylsulfide (DMS) emissions, because DMS emissions influence cloud albedo. This response is closely tied to sea ice through its impacts on marine ecosystem carbon and sulfur cycling, and the ice-albedo feedback implicated in accelerated arctic warming. To reduce the uncertainty in predictions from coupled climate simulations, important model components of the climate system, such as feedbacks between arctic marine biogeochemistry and climate, need to be reasonably and realistically modeled. This research first involved model development to improve the representation of marine sulfur biogeochemistry simulations to understand/diagnose the control of sea-ice-related processes on the variability of DMS dynamics. This study will help build GCM predictions that quantify the relative current and possible future influences of arctic marine ecosystems on the global climate system. Our overall research objective was to improve arctic marine biogeochemistry in the Community Climate System Model (CCSM, now CESM). Working closely with the Climate Ocean Sea Ice Model (COSIM) team at Los Alamos National Laboratory (LANL), we added 1 sea-ice algae and arctic DMS production and related biogeochemistry to the global Parallel Ocean Program model (POP) coupled to the LANL sea ice model (CICE). Both CICE and POP are core components of CESM. Our specific research objectives were: 1) Develop a state-of-the-art ice-ocean DMS model for application in climate models, using observations to constrain the most crucial parameters; 2) Improve the global marine sulfur model used in CESM by including DMS biogeochemistry in the Arctic; and 3) Assess how sea ice influences DMS dynamics in the arctic marine environment and predict how it will do so in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Evaluating Variable‐Resolution CESM Over China and Western United States for Use in Water‐Energy Nexus and Impacts Modeling

Abstract Climate models are critical tools to study earth system processes and are often further downscaled to provide refined‐resolution data sets for regional water‐energy impact analyses. In this study, the Variable‐Resolution Community Earth System Model (VR‐CESM), a new dynamical downscaling method, is employed to generate 1/8° simulations for China and the western United States over 1970–2006. Precipitation, temperature, snowpack, radiation, and wind speed are compared with two 1° global climate models, regional climate model ensemble, and reference data sets to evaluate their fidelity. Simulated precipitation skill is dependent upon the reference data sets used, a slight (<+10%) and spatially consistent wet bias in China during summer and the western United States during winter. Precipitation bias in VR‐CESM is the smallest among models and demonstrates the added value provided by resolution refinement. However, temperature biases are generally greater than precipitation due to more complicated interactions among processes. VR‐CESM simulates +2°C warm bias in the low‐elevation regions in China but −2°C cold bias in mountains. However, DJF cold bias (−2.23°C to−3.37°C) and JJA warm bias (+1.13°C to +1.87°C) exist in the western United States. The modeling skills of precipitation and temperature at various topographies are similar in the two evaluated regions. The cold bias was likely affected by downward shortwave radiation deficit (−15%) and slow bias of surface wind speeds (−16% to −29%). Despite the wet and cold bias, snow water equivalent and snow cover are underestimated in mountains. We conclude that VR‐CESM outperforms other models evaluated and provides the best estimation of downscaled climate model data for water‐energy studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The Earth Model Column Collaboratory (EMC 2 ) v1.1: an open-source ground-based lidar and radar instrument simulator and subcolumn generator for large-scale models

Abstract. Climate models are essential for our comprehensive understanding of Earth's atmosphere and can provide critical insights on future changes decades ahead. Because of these critical roles, today's climate models are continuously being developed and evaluated using constraining observations and measurements obtained by satellites, airborne, and ground-based instruments. Instrument simulators can provide a bridge between the measured or retrieved quantities and their sampling in models and field observations while considering instrument sensitivity limitations. Here we present the Earth Model Column Collaboratory (EMC2), an open-source ground-based lidar and radar instrument simulator and subcolumn generator, specifically designed for large-scale models, in particular climate models, but also applicable to high-resolution model output. EMC2 provides a flexible framework enabling direct comparison of model output with ground-based observations, including generation of subcolumns that may statistically represent finer model spatial resolutions. In addition, EMC2 emulates ground-based (and air- or space-borne) measurements while remaining faithful to large-scale models' physical assumptions implemented in their cloud or radiation schemes. The simulator uses either single particle or bulk particle size distribution lookup tables, depending on the selected scheme approach, to perform the forward calculations. To facilitate model evaluation, EMC2 also includes three hydrometeor classification methods, namely, radar- and sounding-based cloud and precipitation detection and classification, lidar-based phase classification, and a Cloud Feedback Model Intercomparison Project Observational Simulator Package (COSP) lidar simulator emulator. The software is written in Python, is easy to use, and can be straightforwardly customized for different models, radars, and lidars. Following the description of the logic, functionality, features, and software structure of EMC2, we present a case study of highly supercooled mixed-phase cloud based on measurements from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE). We compare observations with the application of EMC2 to outputs from four configurations of the NASA Goddard Institute for Space Studies (GISS) climate model (ModelE3) in single-column model (SCM) mode and from a large-eddy simulation (LES) model. We show that two of the four ModelE3 configurations can form and maintain highly supercooled precipitating cloud for several hours, consistent with observations and LES. While our focus is on one of these ModelE3 configurations, which performed slightly better in this case study, both of these configurations and the LES results post-processed with EMC2 generally provide reasonable agreement with observed lidar and radar variables. As briefly demonstrated here, EMC2 can provide a lightweight and flexible framework for comparing the results of both large-scale and high-resolution models directly with observations, with relatively little overhead and multiple options for achieving consistency with model microphysical or radiation scheme physics.

58 GEOSCIENCES↗
DOE OSTI2011

ESG-CET Final Progress Title

Drawing to a close after five years of funding from DOE's ASCR and BER program offices, the SciDAC-2 project called the Earth System Grid (ESG) Center for Enabling Technologies has successfully established a new capability for serving data from distributed centers. The system enables users to access, analyze, and visualize data using a globally federated collection of networks, computers and software. The ESG software - now known as the Earth System Grid Federation (ESGF) - has attracted a broad developer base and has been widely adopted so that it is now being utilized in serving the most comprehensive multi-model climate data sets in the world. The system is used to support international climate model intercomparison activities as well as high profile U.S. DOE, NOAA, NASA, and NSF projects. It currently provides more than 25,000 users access to more than half a petabyte of climate data (from models and from observations) and has enabled over a 1,000 scientific publications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Simulating Hurricane Katrina in the Simple Cloud‐Resolving E3SM Atmosphere Model v1

Climate models are important tools for advancing understanding and prediction of tropical cyclones (TCs). Traditional global climate models, however, do not have the ability to properly simulate TC intensity due to their coarse horizontal resolution. Regional models can be run at convection‐permitting resolutions, but these models are often strongly influenced by the data used in the lateral boundary forcing, and domain choice can have a large impact on the simulation. Cloud‐resolving global climate models have demonstrated great potential for realism in TC simulations, and in this study we focus specifically on the Simple Cloud‐Resolving Energy Exascale Earth System Model (E3SM) Atmosphere Model (SCREAM) v1 configuration. We evaluate SCREAMv1 against the observational record and the Weather Research and Forecasting (WRF) model run at a convection‐permitting resolution with Hurricane Katrina as our case study. We found that both models produced realistic simulations of Hurricane Katrina. SCREAMv1 demonstrated skill in simulating TC track, size, and intensity, while the model produced an excessive amount of precipitation. In comparison, WRF more accurately simulated TC precipitation and intensity, although the TC wind extent was smaller than the observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

PMEL contributions to the collaboration: SCALING THE EARTH SYSTEM GRID TO PETASCALE DATA for the DOE SciDACs Earth System Grid Center for Enabling Technologies

Drawing to a close after five years of funding from DOE's ASCR and BER program offices, the SciDAC-2 project called the Earth System Grid (ESG) Center for Enabling Technologies has successfully established a new capability for serving data from distributed centers. The system enables users to access, analyze, and visualize data using a globally federated collection of networks, computers and software. The ESG software now known as the Earth System Grid Federation (ESGF) has attracted a broad developer base and has been widely adopted so that it is now being utilized in serving the most comprehensive multi-model climate data sets in the world. The system is used to support international climate model intercomparison activities as well as high profile U.S. DOE, NOAA, NASA, and NSF projects. It currently provides more than 25,000 users access to more than half a petabyte of climate data (from models and from observations) and has enabled over a 1,000 scientific publications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Improved Decarbonization Planning through Climate Resiliency Modeling

California has set ambitious decarbonization goals concerning both emissions and the portion of energy generated by renewable resources. However, climate change poses considerable uncertainties. Variation in load is driven both by the level of electrification as well as the impact of climate change on weather. Further, climate change stands to make weather more variable, impacting not just load but generation from renewable resources. In this paper, we approach the issue of the impacts of climate change on decarbonization planning from two perspectives. First, we look at the range of decarbonization pathways through 8 pathways that account for differences in socioeconomic development, global emissions, and warming. Second, we develop a more robust way of ensuring the reliability of energy resources planning than the commonly used planning reserve margin. We show that the proposed method can save between 6 and 14 billion dollars in investment and maintenance costs and outline critical policy implications concerning the reliance of power plants for satisfying planning reliability requirements, including the potential retirement of dozens of peaker power plants.

Anderson, Osten P.↗
DOE OSTI2013

Incorporation of the HYbrid Coordinate Ocean Model (HYCOM) into the Community Climate System Model (CCSM): Evaluation and Climate Applications (Final Report for DOE Grant DE-FG02-07ER64470)

The primary goal of the project entitled “Incorporation of the HYbrid Coordinate Ocean Model (HYCOM) into the Community Climate System Model (CCSM): Evaluation and Climate Applications” was to systematically investigate the performance of the HYbrid Coordinate Ocean Model (HYCOM) as an alternative oceanic component of the NCAR’s Community Climate System Model (CCSM). We have configured two versions of the fully coupled CCSM3/HYCOM: one with a medium resolution (T42) Community Atmospheric Model (CAM) and the other with higher resolution (T85). We have performed a comprehensive analysis of the 400-year fully coupled CCSM3/HYCOM simulations and compared the results with those from CCSM3/POP and with climatological observations, and also we have performed tuning of critical model parameters, including Smagorinsky viscosity, isopycnal diffusivity, and background vertical diffusivity. The analysis shows that most oceanic features are well represented in the CCSM3/HYCOM. The coupled CCSM3/HYCOM (T42) has been integrated for 400 years, and the results have been archived and transferred to the High Performance Computer in the Florida State Univesity. In the last year, we have made comprehensive diagnostics of the long-term simulations by the comparison with the original CCSM3/POP simulation and with the observations. To gain some understanding of the model biases, the mean climate and modes of climate variability of the two models are compared with observations. The examination includes the Northern and Southern Annular Modes (NAM and SAM), the Pacific-North-American (PNA) pattern, the Atlantic Multidecadal Oscillation (AMO), and the main Southern Ocean SST mode. We also compared the performance of ENSO simulation in the coupled models. This report summarizes the main findings from the comparison of long-term CCSM3/HYCOM and CCSM3/POP simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

ISMIP6-based Antarctic projections to 2100: simulations with the BISICLES ice sheet model

The contribution of the Antarctic Ice Sheet is one of the most uncertain components of sea level rise to 2100. Ice sheet models are the primary tool for projecting future sea level contribution from continental ice sheets. The Ice Sheet Model Intercomparison for the Coupled Model Intercomparison Phase 6 (ISMIP6) provided projections of the ice sheet contribution to sea level over the 21st century, quantifying uncertainty due to ice sheet model, climate model, emission scenario, and uncertain parameters. We present simulations following the ISMIP6 framework with the BISICLES ice sheet model and new experiments extending the ISMIP6 protocol to more comprehensively sample uncertainties in future climate, ice shelf sensitivity to ocean melting, and their interactions. These results contributed to the land ice projections of Edwards et al. (2021), which formed the basis of sea level projections for the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (AR6). Our experiments show the important interplay between surface mass balance processes and ocean-driven melt in determining Antarctic sea level contribution. Under higher-warming scenarios, high accumulation offsets more ocean-driven mass loss when sensitivity to ocean-driven melt is low. Conversely, we show that when sensitivity to ocean warming is high, ocean melting drives increased mass loss despite high accumulation. Overall, we simulate a sea level contribution range across our experiments from 2 to 178 mm. Finally, we show that collapse of ice shelves due to surface warming increases sea level contribution by 25 mm relative to the no-collapse experiments, for both moderate and high sensitivity of ice shelf melting to ocean forcing.

54 ENVIRONMENTAL SCIENCES↗