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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Application-specific optimal model weighting of global climate models: A red tide example

Global climate models (GCMs) and Earth system models (ESMs) provide many climate services with environmental relevance. The High Resolution Model Inter-comparison Project (HighResMIP) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) provides model runs of GCMs and ESMs to address regional phenomena. Developing a parsimonious ensemble of CMIP6 requires multiple ensemble methods such as independent-model subset selection, prescreening-based subset selection, and model weighting. The work presented here focuses on application-specific optimal model weighting, with prescreening-based subset selection. As such, independent ensemble members are categorized, selected, and weighted based on their ability to reproduce physically-interpretable features of interest that are problem-specific. We discuss the strengths and caveats of optimal model weighting using a case study of red tide prediction in the Gulf of Mexico along the West Florida Shelf. Red tide is a common name of specific harmful algal blooms that occur worldwide, causing adverse socioeconomic and environmental impacts. Our results indicate the importance of prescreening-based subset selection as optimal model weighting can underplay robust ensemble members by optimizing error cancellation. Prescreening-based subset selection also provides insights about the validity of the model weights. By illustrating the caveats of using non-representative models when optimal model weighting is used, the findings and discussion of this study are pertinent to many other climate services.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Evaluation of regional transport of PM2.5 during severe atmospheric pollution episodes in the western Yangtze River Delta, China

During winter 2018, the 16 prefecture-level cities in Anhui Province, Western Yangtze River Delta region, China had very high PM2.5 concentrations and prolonged pollution days. The impact of regional transport in the formation, accumulation, as well as dispersion of fine particulate matter (PM2.5) in Anhui Province was very significant. This study quantified and analyzed the vertical transport of PM2.5 in three major cities (Hefei, Fuyang, and Suzhou) of Anhui Province in January and July 2018 using the Weather Research and Forecasting (WRF) model coupled with the Community Multiscale Air Quality (CMAQ) model. The results of the inter-regional transport of PM2.5 revealed the dominant transport pathways for the three cities. The flux mainly flowed into Fuyang from Henan (2.23 and 1.42 kt/day in January and July, respectively) and Bozhou (1.96 and 1.21 kt/day in January and July, respectively), while the main flux from Fuyang flowed into Henan (-2.15 kt/day) and Lu'an (-1.91 kt/day) in January and Henan (-0.34 kt/day) and Bozhou (-0.29 kt/day) in July. In addition, the dominant transport pathways and the heights at which they occurred were identified: the northwest-southeast and northeast-south pathways in both winter and summer at both lower (?300 m) and higher (=300 m) levels for Fuyang; the northwest-south and northeast-southwest pathways in winter (at both lower and upper levels) and northwest-east and northeast-southwest pathways in summer at lower and upper levels for Hefei; and the northwest-southeast and northeast-south pathways in both winter (from 50 m up to the top level) and summer (between 100 and 300 m) for Suzhou. Furthermore, the intensities of daily PM2.5 transport fluxes in Fuyang during the atmospheric pollution episode (APE1) were stronger than the monthly average. These results show that joint emission controls across multiple cities along the identified pathways are urgently needed to reduce winter episodes.

Sulaymon, Ishaq D.↗
DOE OSTI2024

Component innovations for lower cost mechanical vapor compression

Despite significant capital and operating costs, mechanical vapor compression (MVC) remains the preferred technology for challenging brine concentration applications. Here, this work seeks to assess the dependence of MVC costs on feedwater salinity and desired water recovery and to quantify the value of improved component performance or reduced component costs for reducing the levelized cost of water (LCOW) of MVC. We built a cost optimization model coupling thermophysical, heat and mass transfer, and technoeconomic models to optimize and identify low cost MVC system designs as a function of feedwater salinity and water recovery. The LCOW ranges over 3.6 to 6.1 $\$$/m 3 for seawater feed salinities of 25–150 g/kg and water recoveries of 40–80 %. We then perform sensitivity analysis on parameter inputs to isolate irreducible costs and determine high value component innovation targets. The LCOW was most sensitive to evaporator material costs and performance, including the overall heat transfer coefficient in the evaporator. Process and material innovations such as polymer-composite evaporator tubes that reduce evaporator costs by 25 % without reducing heat transfer performance by more than 10 % would result in MVC cost reductions of 8 %.

42 ENGINEERING↗
DOE OSTI2024

Structural Uncertainty in the Sensitivity of Urban Temperatures to Anthropogenic Heat Flux

One key source of uncertainty for weather and climate models is structural uncertainty arising from the fact that these models must simplify or approximate complex physical, chemical, and biological processes that occur in the real world. However, structural uncertainty is rarely examined in the context of simulated effects of anthropogenic heat flux in cities. Using the Weather Research and Forecasting (WRF) model coupled with a single-layer urban canopy model, it is found that the sensitivity of urban canopy air temperature to anthropogenic heat flux can differ by an order of magnitude depending on how anthropogenic heat flux is released to the urban environment. Moreover, varying model structures through changing the treatment of roof-air interaction and the parameterization of convective heat transfer between the canopy air and the atmosphere can affect the sensitivity of urban canopy air temperature by a factor of 4. Urban surface temperature and 2-m air temperature are less sensitive to the methods of anthropogenic heat flux release and the examined model structural variants than urban canopy air temperature, but their sensitivities to anthropogenic heat flux can still vary by as much as a factor of 4 for surface temperature and 2 for 2-m air temperature. Our study recommends using temperature sensitivity instead of temperature response to understand how various physical processes (and their representations in numerical models) modulate the simulated effects of anthropogenic heat flux.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Quantifying contributions of natural variability and anthropogenic forcings on increased fire weather risk over the western United States

Previous studies have identified a recent increase in wildfire activity in the western United States (WUS). However, the extent to which this trend is due to weather pattern changes dominated by natural variability versus anthropogenic warming has been unclear. Using an ensemble constructed flow analogue approach, we have employed observations to estimate vapor pressure deficit (VPD), the leading meteorological variable that controls wildfires, associated with different atmospheric circulation patterns. Our results show that for the period 1979 to 2020, variation in the atmospheric circulation explains, on average, only 32% of the observed VPD trend of 0.48 ± 0.25 hPa/decade (95% CI) over the WUS during the warm season (May to September). The remaining 68% of the upward VPD trend is likely due to anthropogenic warming. The ensemble simulations of climate models participating in the sixth phase of the Coupled Model Intercomparison Project suggest that anthropogenic forcing explains an even larger fraction of the observed VPD trend (88%) for the same period and region. These models and observational estimates likely provide a lower and an upper bound on the true impact of anthropogenic warming on the VPD trend over the WUS. During August 2020, when the August Complex “Gigafire” occurred in the WUS, anthropogenic warming likely explains 50% of the unprecedented high VPD anomalies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Climate change penalty and benefit on surface ozone: a global perspective based on CMIP6 earth system models

Abstract This work presents an analysis of the effect of climate change on surface ozone discussing the related penalties and benefits around the globe from the global modelling perspective based on simulations with five CMIP6 (Coupled Model Intercomparison Project Phase 6) Earth System Models. As part of AerChemMIP (Aerosol Chemistry Model Intercomparison Project) all models conducted simulation experiments considering future climate (ssp370SST) and present-day climate (ssp370pdSST) under the same future emissions trajectory (SSP3-7.0). A multi-model global average climate change benefit on surface ozone of −0.96 ± 0.07 ppbv °C −1 is calculated which is mainly linked to the dominating role of enhanced ozone destruction with higher water vapour abundances under a warmer climate. Over regions remote from pollution sources, there is a robust decline in mean surface ozone concentration on an annual basis as well as for boreal winter and summer varying spatially from −0.2 to −2 ppbv °C −1 , with strongest decline over tropical oceanic regions. The implication is that over regions remote from pollution sources (except over the Arctic) there is a consistent climate change benefit for baseline ozone due to global warming. However, ozone increases over regions close to anthropogenic pollution sources or close to enhanced natural biogenic volatile organic compounds emission sources with a rate ranging regionally from 0.2 to 2 ppbv C −1 , implying a regional surface ozone penalty due to global warming. Overall, the future climate change enhances the efficiency of precursor emissions to generate surface ozone in polluted regions and thus the magnitude of this effect depends on the regional emission changes considered in this study within the SSP3_7.0 scenario. The comparison of the climate change impact effect on surface ozone versus the combined effect of climate and emission changes indicates the dominant role of precursor emission changes in projecting surface ozone concentrations under future climate change scenarios.

Zanis, Prodromos↗
DOE OSTI2025

Effectiveness of street trees in reducing air temperature and outdoor heat exposure in Las Vegas

Urban greening and especially tree planting strategies are being widely planned and implemented to mitigate urban overheating and thermal stress in many urban areas. However, the effectiveness of these strategies depends on multiple factors, including urban morphology, environmental conditions, and tree characteristics. This study investigates the effects of street tree planting strategies on air temperature and outdoor heat exposure in Las Vegas by combining an urbanized mesoscale climate model coupled to a multi-layer street tree model (Weather Research and Forecasting-BEP-Tree; Δ x = 900 m) with a microscale pedestrian heat exposure model (Temperatures of Urban Facets for Pedestrian; Δ x = 1 m). A series of simulations are conducted for July and August 2022. Large city-wide increases of a drought tolerant tree species cool air temperature mainly during the nighttime (up to 1.5 °C), with daytime effects being limited due to leaves shedding sensible instead of latent heat as stomata close in response to high vapor pressure deficits. Increased evaporative cooling is achieved with a different tree species (double at night, and reaching 0.4 °C during the day), but water requirements increase threefold. Despite their relatively small effect on air temperature during the day, trees provide significant shade by intercepting solar radiation, reducing mean radiant temperature (up to 16 °C) and enhancing outdoor thermal comfort, a major benefit of street trees in hot arid climates. The nighttime cooling of trees and the daytime reduction of radiant loading show potential to reduce the heat-related health impacts. Our results highlight the need to evaluate the effects of street trees on a case-by-case basis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Exploring the impacts of a national U.S. CO 2 tax and revenue recycling options with a coupled electricity-economy model

This paper provides a comprehensive exploration of the impacts of economy-wide CO 2 taxes in the U.S. simulated using a detailed electric sector model [the National Renewable Energy Laboratory's Regional Energy Deployment System (ReEDS)] linked with a computable general equilibrium model of the U.S. economy [the Massachusetts Institute of Technology's U.S. Regional Energy Policy (USREP) model]. We implement various tax trajectories and options for using the revenue collected by the tax and describe their impact on household welfare and its distribution across income levels. Overall, we find that our top-down/bottom-up models affects estimates of the distribution and cost of emission reductions as well as the amount of revenue collected, but that these are mostly insensitive to the way the revenue is recycled. We find that substantial abatement opportunities through fuel switching and renewable penetration in the electricity sector allow the economy to accommodate extensive emissions reductions at relatively low cost. While welfare impacts are largely determined by the choice of revenue recycling scheme, all tax levels and schemes provide net benefits when accounting for the avoided global climate change benefits of emission reductions. Recycling revenue through capital income tax rebates is more efficient than labor income tax rebates or uniform transfers to households. While capital tax rebates substantially reduce the overall costs of emission abatement, they profit high income households the most and are regressive. We more generally identify a clear trade-off between equity and efficiency across the various recycling options. However, we show through a set of hybrid recycling schemes that it is possible to limit inequalities in impacts, particularly those on the lowest income households, at relatively little incremental cost.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Observational Data for Next-Generation Climate Model Evaluation: Requirements, Considerations, and Best Practices

Climate model simulations are an important source of information about our planet’s climate system and also enable informed decision-making under different future scenarios. As a new archive of results from the next generation of climate models is anticipated to become available with the Coupled Model Intercomparison Project phase 7 (CMIP7), the need to develop efficient and robust methods to evaluate models is paramount. Observations are an integral part of model evaluation, providing a means to quantify and understand the degree to which climate models can faithfully reproduce Earth system processes. Such analysis is critical for constraining climate projections, identifying areas of focus for model development, and assisting analysts in deciphering the utility of models for specific applications. Observations of Earth system come from a diversity of sources, span different space–time domains, and are produced by different communities, and each dataset features different data structures and formats, metadata standards, and its own unique uncertainties. Uncertainties in an observational dataset may stem from gaps in temporal and spatial coverage, instrumentation errors, or assumptions in retrieval and processing methods. How then does one ensure that observational data are ready for use and utilized in the most appropriate way for robust, rapid, and routine climate model evaluation? The CMIP7 Model Benchmarking Task Team with input from the broader climate modeling, model evaluation, and observational data communities present a vision and considerations for best practices toward the optimal and appropriate use of observational data to support next-generation climate model evaluation.

Climate models↗
DOE OSTI2016

Metrics for the Diurnal Cycle of Precipitation: Toward Routine Benchmarks for Climate Models

In this paper, metrics are proposed—that is, a few summary statistics that condense large amounts of data from observations or model simulations—encapsulating the diurnal cycle of precipitation. Vector area averaging of Fourier amplitude and phase produces useful information in a reasonably small number of harmonic dial plots, a procedure familiar from atmospheric tide research. The metrics cover most of the globe but down-weight high-latitude wintertime ocean areas where baroclinic waves are most prominent. This enables intercomparison of a large number of climate models with observations and with each other. The diurnal cycle of precipitation has features not encountered in typical climate model intercomparisons, notably the absence of meaningful “average model” results that can be displayed in a single two-dimensional map. Displaying one map per model guides development of the metrics proposed here by making it clear that land and ocean areas must be averaged separately, but interpreting maps from all models becomes problematic as the size of a multimodel ensemble increases. Global diurnal metrics provide quick comparisons with observations and among models, using the most recent version of the Coupled Model Intercomparison Project (CMIP). This includes, for the first time in CMIP, spatial resolutions comparable to global satellite observations. Finally, consistent with earlier studies of resolution versus parameterization of the diurnal cycle, the longstanding tendency of models to produce rainfall too early in the day persists in the high-resolution simulations, as expected if the error is due to subgrid-scale physics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

DVMDOSTEM v0.8.3: a terrestrial ecosystem model designed to represent arctic, boreal and permafrost ecosystem dynamics

The impacts of climate change on natural ecosystems are the result of complex physical and ecological processes operating and interacting at a variety of spatio-temporal scales, that can be represented in process-based ecosystem models. DVMDOSTEM is an advanced process-based terrestrial ecosystem model (TEM) designed to study ecosystem responses to climate changes and disturbances. It has a particular focus on permafrost regions (i.e. regions characterized by soils that stay partially frozen all year round for at least two consecutive years), encompassing boreal, arctic, and alpine landscapes. The model couples two previous versions of the Terrestrial Ecosystem Model (TEM) (McGuire et al., 1992): DVMTEM that includes a dynamic vegetation module (DVM) (E. S. Euskirchen et al., 2009), and DOSTEM that includes a dynamic organic soil module (DOS) (H. Genet et al., 2013; Yi et al., 2010). DVMDOSTEM simulates processes at yearly and monthly scales, with some physical processes operating at an even finer temporal resolution. Its versatility allows for site-specific to regional simulations, making it valuable for predicting shifts in permafrost, vegetation, and carbon (C) and nitrogen (N) dynamics. While DVMDOSTEM has been described in the methods sections of many manuscripts, this paper is the first stand alone description of DVMDOSTEM, independent of a particular scientific investigation.

Carman, Tobey B. [Univ. of Alaska, Fairbanks, AK (↗
DOE OSTI2018

Confronting Models with Regional CO 2 Observations

This research addressed an important DOE science area: the role of natural disturbances in carbon cycling. Our project included both (a) modeling and field measurements and (b) strengthened ties between DOE national laboratories and universities which continue after the project was completed. Our focus was on understanding the consequences of drought and emissions (fire and urban) to atmospheric trace gas composition (carbon dioxide, carbon monoxide, and methane), including both concentration and stable isotope composition. Measurements of these atmospheric gases were used to infer the spatial and temporal patterns of both sources and sinks in the carbon cycle. As part of this effort, we maintained two long-term monitoring networks along a geographic gradient in Utah and Colorado that spans montane forests, urban regions, and oil/gas fields. In this research, we expanded on a well-accepted atmospheric model (STILT-WRF) as a tool to evaluate fluxes in CLM/CESM-related models. We used the STILT model to provide a strong linkage between point atmospheric measurements and the surface parameterizations/emissions that are part of the CLM/CESM models. Overall, this project benefited and supported the DOE Long Term Mission and Goals in four distinct ways: (a) testing of carbon cycle models, (b) testing and evaluating model mechanisms whereby factors in CLM influence trace gas composition in CESM, (c) acquiring high-quality, long-term data on concentrations of carbon dioxide in western USA ecosystems, and (d) by reducing uncertainties associated with the representation of climate-carbon feedbacks in Earth System models through the development of new methods for evaluating model performance. One postdoctoral associate (Henrique Duarte) and one Ph.D. student (Darek Malia) were trained with this support. Nine peer-reviewed publications and 14 poster presentations were produced with support from this project. This proposal addresses a specific science area in the RFP: the role of natural disturbances in carbon cycling. In particular, we will focus on the consequences of drought and fire at landscape to regional scales for atmospheric trace gas concentration and stable isotope composition (CO 2 , CO, and CH 4 ). We seek to expand on the well accepted atmospheric Stochastic Time-Inverted Lagrangian Transport (STILT) model coupled to the Weather Research and Forecasting (WRF) model as a tool to evaluate stable isotope fluxes in CLM/CESM-related models through existing, long-term data sets and field campaigns where high-precision trace gas concentration and isotope measurements can be made along gradients and transects. Given the confounding impacts of anthropogenic trace gas emissions on landscape-to-regional atmospheric observations, we will also measure and parameterize isotopic characteristics of CO 2 , CO, and CH 4 from anthropogenic or forest sources in order to allow us the opportunity to partition atmospheric trace gases into natural and anthropogenic sources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Liquid Piston with Spray Cooling Near-Isothermal Compressor

The goal of this project was to prototype and characterize the performance of a liquid-piston spray-cooled gas compressor. The working principle of the compressor enables optimized high-efficiency operation over a very wide range of operating conditions, unlike conventional compressors that are optimized for a narrow range of operating conditions. The compressor technology is suitable for many applications, such as gas pipeline transport, gas storage, and commercial and residential heat pumps. Both physical testing and computational fluid dynamics (CFD) modeling of the processes using the Oak Ridge National Laboratory high-performance computing center were completed. The experimental and CFD studies focused on a near-isothermal liquid-piston compressor (LPC) that uses propylene glycol to compress CO 2 . The first prototype demonstrated isothermal operation during several sequentially executed cycles of CO 2 compression and raised the temperature of the compressed CO 2 by only 2 K, compared with approximately 6 K when the gas was compressed non-isothermally. Isothermal operation was demonstrated at CO 2 flow rates of up to 2 L/min. The second prototype was designed with two compression chambers to allow continuous flow of high-pressure CO 2 . However, the design of the valve train to direct flow between the compression chambers was not sufficient to allow demonstration of CO 2 compression. Numerical simulations of the LPC in which the compression chamber was filled with propylene glycol injected from the bottom inlet were performed using large eddy simulation (LES) with the wall-adapting local eddy-viscosity subgrid-scale model coupled with the multiphase volume of fluid (VOF) model to simulate the transient interface between gas and liquid and to capture the heat and mass transfers within the compression chamber. In this effort, the effects of boundary conditions applied to the LES-VOF calculations (i.e., no wall, an adiabatic wall, and a wall with a heat flux subscribed) on the overall pressure and temperature of the CO 2 gas as well as the transient evolution of flow and heat transfer within the compression chamber were investigated and are discussed in this report. The LES calculation with no wall showed no dynamical flow patterns, and the volume-averaged temperature of CO 2 increased from 305 to 392.7 K, whereas LES calculations with a constant wall temperature or a wall heat flux had similar increases of CO 2 temperatures. The results of the LES simulation using a wall heat flux showed different stages in the compression process and revealed dynamical formation and interaction of CO 2 gas layers and circulation flow patterns within the chamber that contributed to the overall heat transfer between the solid wall, gas, and liquid surface in the compressor. Though an industrial partnership for commercializing the compressor was not secured, the technology was attractive for an industrial partner to use in two research proposals in response to US Department of Energy funding opportunity announcements.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Arctic Amplification in the Community Earth System Models (CESM1 and CESM2)

We compare the Arctic amplification (AA) produced by the two Community Earth System Models CESM1 and CESM2, members of the CEMIP5 (Coupled Models Intercomparison Project phase 5) and CEMIP6 collections, respectively. We find that the CESM1 model reproduces the recent high values of the AA deduced from the observed temperature much better than the CESM2. The correlation coefficient within the 1970–2012 time period between CESM1-simulated AA and the observed one is 0.47, while the CESM2 simulation leads to an anticorrelation of r = –0.53. Even the more successful model (CESM1) is not able to reproduce recent high AA values of 4–5. The main cause of this failure is the model’s overestimate of the rate of increase in the mean global temperature in years post 1990. When the CESM1 model’s simulated trend of the mean global temperature is replaced in the expression for the AA by the observed temperature trend, the correlation coefficient increases from 0.47 to 0.75. The CESM1 model is among the best north American models in AA simulation while the CESM2 model is among the least successful.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Aerosol Impacts on California Winter Clouds and Precipitation during CalWater 2011: Local Pollution versus Long-Range Transported Dust

Mineral dust aerosols often observed over California in winter and spring, associated with long-range transport from Asia and Sahara, have been linked to enhanced precipitation based on observations. Local anthropogenic pollution, on the other hand, was shown in previous observational and modeling studies to reduce precipitation. Here we incorporate recent developments in ice nucleation parameterizations to link aerosols with ice crystal formation in a spectral-bin cloud microphysical model coupled with the Weather Research and Forecasting (WRF) model, to examine the relative and combined impacts of dust and local pollution particles on cloud properties and precipitation type and intensity. Simulations are carried out for two cloud cases with contrasting meteorology and cloud dynamics that occurred on February 16 (FEB16) and March 02 (MAR02) from the CalWater 2011 field campaign. In both cases, observations show the presence of dust and biological particles in a relative pristine environment. The simulated cloud microphysical properties and precipitation show reasonable agreement with aircraft and surface measurements. Model sensitivity experiments indicate that in the pristine environment, the dust and biological aerosol layers increase the accumulated precipitation by 10-20% from the Central Valley to the Sierra Nevada Mountains for both FEB16 and MAR02 due to a ~40% increase in snow formation, validating the observational hypothesis. Model results show that local pollution increases precipitation over the windward slope of the mountains by few percent due to increased snow formation when dust is present but reduces precipitation by 5-8% if dust is removed on FEB16. The effects of local pollution on cloud microphysics and precipitation strongly depend on meteorology including the strength of the Sierra Barrier Jet, and cloud dynamics. This study further underscores the importance of the interactions between local pollution, dust, and environmental conditions for assessing aerosol effects on cold season precipitation in California.

aerosol impacts↗
DOE OSTI2017

Urbanization-induced urban heat island and aerosol effects on climate extremes in the Yangtze River Delta region of China

Abstract. The WRF-Chem model coupled with a single-layer urban canopy model (UCM) is integrated for 5 years at convection-permitting scale to investigate the individual and combined impacts of urbanization-induced changes in land cover and pollutant emissions on regional climate in the Yangtze River Delta (YRD) region in eastern China. Simulations with the urbanization effects reasonably reproduced the observed features of temperature and precipitation in the YRD region. Urbanization over the YRD induces an urban heat island (UHI) effect, which increases the surface temperature by 0.53 °C in summer and increases the annual heat wave days at a rate of 3.7 d yr−1 in the major megacities in the YRD, accompanied by intensified heat stress. In winter, the near-surface air temperature increases by approximately 0.7 °C over commercial areas in the cities but decreases in the surrounding areas. Radiative effects of aerosols tend to cool the surface air by reducing net shortwave radiation at the surface. Compared to the more localized UHI effect, aerosol effects on solar radiation and temperature influence a much larger area, especially downwind of the city cluster in the YRD. Results also show that the UHI increases the frequency of extreme summer precipitation by strengthening the convergence and updrafts over urbanized areas in the afternoon, which favor the development of deep convection. In contrast, the radiative forcing of aerosols results in a surface cooling and upper-atmospheric heating, which enhances atmospheric stability and suppresses convection. The combined effects of the UHI and aerosols on precipitation depend on synoptic conditions. Two rainfall events under two typical but different synoptic weather patterns are further analyzed. It is shown that the impact of urban land cover and aerosols on precipitation is not only determined by their influence on local convergence but also modulated by large-scale weather systems. For the case with a strong synoptic forcing associated with stronger winds and larger spatial convergence, the UHI and aerosol effects are relatively weak. When the synoptic forcing is weak, however, the UHI and aerosol effects on local convergence dominate. This suggests that synoptic forcing plays a significant role in modulating the urbanization-induced land-cover and aerosol effects on individual rainfall event. Hence precipitation changes due to urbanization effects may offset each other under different synoptic conditions, resulting in little changes in mean precipitation at longer timescales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

A consistent prescription of stratospheric aerosol for both radiation and chemistry in the Community Earth System Model (CESM1)

Here we describe an updated parameterization for prescribing stratospheric aerosol in the National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM1). The need for a new parameterization is motivated by the poor response of the CESM1 (formerly referred to as the Community Climate System Model, version 4, CCSM4) simulations contributed to the Coupled Model Intercomparison Project 5 (CMIP5) to colossal volcanic perturbations to the stratospheric aerosol layer (such as the 1991 Pinatubo eruption or the 1883 Krakatau eruption) in comparison to observations. In particular, the scheme used in the CMIP5 simulations by CESM1 simulated a global mean surface temperature decrease that was inconsistent with the GISS Surface Temperature Analysis (GISTEMP), NOAA's National Climatic Data Center, and the Hadley Centre of the UK Met Office (HADCRUT4). The new parameterization takes advantage of recent improvements in historical stratospheric aerosol databases to allow for variations in both the mass loading and size of the prescribed aerosol. An ensemble of simulations utilizing the old and new schemes shows CESM1's improved response to the 1991 Pinatubo eruption. Most significantly, the new scheme more accurately simulates the temperature response of the stratosphere due to local aerosol heating. Here, results also indicate that the new scheme decreases the global mean temperature response to the 1991 Pinatubo eruption by half of the observed temperature change, and modelled climate variability precludes statements as to the significance of this change.

58 GEOSCIENCES↗
DOE OSTI2021

A clustering-based approach to ocean model–data comparison around Antarctica

The Antarctic Continental Shelf seas (ACSS) are a critical, rapidly changing element of the Earth system. Analyses of global-scale general circulation model (GCM) simulations, including those available through the Coupled Model Intercomparison Project, Phase 6 (CMIP6), can help reveal the origins of observed changes and predict the future evolution of the ACSS. However, an evaluation of ACSS hydrography in GCMs is vital: previous CMIP ensembles exhibit substantial mean-state biases (reflecting, for example, misplaced water masses) with a wide inter-model spread. Because the ACSS are also a sparely sampled region, grid-point-based model assessments are of limited value. Our goal is to demonstrate the utility of clustering tools for identifying hydrographic regimes that are common to different source fields (model or data), while allowing for biases in other metrics (e.g., water mass core properties) and shifts in region boundaries. We apply K-means clustering to hydrographic metrics based on the stratification from one GCM (Community Earth System Model version 2; CESM2) and one observation-based product (World Ocean Atlas 2018; WOA), focusing on the Amundsen, Bellingshausen and Ross seas. When applied to WOA temperature and salinity profiles, clustering identifies “primary” and “mixed” regimes that have physically interpretable bases. For example, meltwater-freshened coastal currents in the Amundsen Sea and a region of high-salinity shelf water formation in the southwestern Ross Sea emerge naturally from the algorithm. Both regions also exhibit clearly differentiated inner- and outer-shelf regimes. The same analysis applied to CESM2 demonstrates that, although mean-state model biases in water mass T–S characteristics can be substantial, using a clustering approach highlights that the relative differences between regimes and the locations where each regime dominates are well represented in the model. CESM2 is generally fresher and warmer than WOA and has a limited fresh-water-enriched coastal regimes. Given the sparsity of observations of the ACSS, this technique is a promising tool for the evaluation of a larger model ensemble (e.g., CMIP6) on a circum-Antarctic basis.

54 ENVIRONMENTAL SCIENCES↗