Results for “COMMUNITY ATMOSPHERE MODEL” — Page 66

DOE OSTI2016

DMS role in ENSO cycle in the tropics

We examined the multiyear mean and variability of dimethyl sulfide (DMS) and its relationship to sulfate aerosols, as well as cloud microphysical and radiative properties. We conducted a 150 year simulation using preindustrial conditions produced by the Community Earth System Model embedded with a dynamic DMS module. The model simulated the mean spatial distribution of DMS emissions and burden, as well as sulfur budgets associated with DMS, SO 2 , H 2 SO 4 , and sulfate that were generally similar to available observations and inventories for a variety of regions. Changes in simulated sea-to-air DMS emissions and associated atmospheric abundance, along with associated aerosols and cloud and radiative properties, were consistently dominated by El Niño–Southern Oscillation (ENSO) cycle in the tropical Pacific region. Simulated DMS, aerosols, and clouds showed a weak positive feedback on sea surface temperature. This feedback suggests a link among DMS, aerosols, clouds, and climate on interannual timescales. The variability of DMS emissions associated with ENSO was primarily caused by a higher variation in wind speed during La Niña events. As a result, the simulation results also suggest that variations in DMS emissions increase the frequency of La Niña events but do not alter ENSO variability in terms of the standard deviation of the Niño 3 sea surface temperature anomalies.

58 GEOSCIENCES↗

DOE OSTI2017

Evaluations of high-resolution dynamically downscaled ensembles over the contiguous United States

This study uses Weather Research and Forecast (WRF) model to evaluate the performance of six dynamical downscaled decadal historical simulations with 12-km resolution for a large domain (7200 x 6180 km) that covers most of North America. The initial and boundary conditions are from three global climate models (GCMs) and one reanalysis data. The GCMs employed in this study are the Geophysical Fluid Dynamics Laboratory Earth System Model with Generalized Ocean Layer Dynamics component, Community Climate System Model, version 4, and the Hadley Centre Global Environment Model, version 2-Earth System. The reanalysis data is from the National Centers for Environmental Prediction-US. Department of Energy Reanalysis II. We analyze the effects of bias correcting, the lateral boundary conditions and the effects of spectral nudging. We evaluate the model performance for seven surface variables and four upper atmospheric variables based on their climatology and extremes for seven subregions across the United States. The results indicate that the simulation’s performance depends on both location and the features/variable being tested. We find that the use of bias correction and/or nudging is beneficial in many situations, but employing these when running the RCM is not always an improvement when compared to the reference data. The use of an ensemble mean and median leads to a better performance in measuring the climatology, while it is significantly biased for the extremes, showing much larger differences than individual GCM driven model simulations from the reference data. This study provides a comprehensive evaluation of these historical model runs in order to make informed decisions when making future projections.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Intensification of the Pre-Meiyu Rainband in the Late 21st Century

Increased atmospheric moisture content and changing land-ocean thermal contrasts are usually implicated in the East Asian summer rainfall response to global warming. We highlight an additional influence whereby increased meridional stationary eddy circulation downstream of the Tibetan Plateau drives a stronger moisture flux convergence over southeastern China, intensifying the early summer rainband. This effect occurs robustly across the Community Earth System Model large ensemble Representative Control Pathway 8.5 simulations, and only for its pre-Meiyu stage (mid-May through late June). The westerly jet impinging on the Plateau is also enhanced, suggesting an orographic influence on the westerlies as the root cause. The increased westerlies result from warmer tropical tropospheric temperatures that enhance the meridional temperature gradient at the latitudes of the Plateau. Finally, our results highlight the potential role of the westerlies in altering the East Asian early summer monsoon rainfall in the late 21st century.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Climate Base State Influences on South Asian Monsoon Processes Derived From Analyses of E3SMv2 and CESM2

Abstract The effects of differences in climate base state are related to processes associated with the present‐day South Asian monsoon simulations in the Energy Exascale Earth System Model version 2 (E3SMv2) and the Community Earth System Model version 2 (CESM2). Though tropical Pacific and Indian Ocean base state sea surface temperatures (SSTs) are over 1°C cooler in E3SMv2 compared to CESM2, and there is an overall reduction of Indian sector precipitation, the pattern of South Asian monsoon precipitation is similar in the two models. Monsoon‐ENSO teleconnections, dynamically linked by the large‐scale east‐west atmospheric circulation, are reduced in E3SMv2 compared to CESM2. In E3SMv2, this is related to cooler tropical SSTs and ENSO amplitude that is less than half that in CESM2. Comparison to a tropical Pacific pacemaker experiment shows, to a first order, that the base state SSTs and ENSO amplitude contribute roughly equally to lower amplitude monsoon‐ENSO teleconnections in E3SMv2.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Delayed coastal inundations caused by ocean dynamics post-Hurricane Matthew

Post Hurricane Abnormal Water Level (PHAWL) poses a persistent inundation threat to coastal communities, yet unresolved knowledge gaps exist regarding its spatiotemporal impacts and causal mechanisms. Using a high-resolution coastal model with a set of observations, we find that the PHAWLs are up to 50 cm higher than the normal water levels for several weeks and cause delayed inundations around residential areas of the U.S. Southeast Coast (USSC). Numerical experiments reveal that while atmospheric forcing modulates the coastal PHAWLs, ocean dynamics primarily driven by the Gulf Stream control the mean component and duration of the shelf-scale PHAWLs. Because of the large spatial impact of the post-hurricane oceanic forcing, the coastal hazards are not limited to a direct hit from a hurricane but can be detected throughout the USSC where the oceanic processes reach.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

How Frequent Will the Rarest Daily Rainfall Records of Hurricane Ida’s Remnants Be in the Future?

Abstract Gaining continued insights into the impact of global warming on the occurrence of hurricane-associated intense record downpours is essential for building climate resilient communities. This study investigates projected future changes in extreme rainfall over the Northeast United States, as represented by extreme daily amounts during Hurricane Ida in 2021. We used historical control simulations of Weather Research and Forecasting (WRF) Model generated from 40 years of weather events (1980–2014, 12 km) forced by the fifth generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis. These simulations are thermodynamically modified (2060–2100) via an imposed warming for the high-emission scenario of shared socioeconomic pathway (SSP585) from a range of general circulation models. Ground observations from the Global Historical Climatology Network (1950–2014) and WRF simulations (historical, 1980–2014, and future, 2060–2100) are integrated into a nonstationary generalized extreme value (GEV) framework to assess the frequency of Ida’s heaviest daily rain rates under the SSP585 scenario. Results show that Ida’s daily maximum rainfall recorded at different observation locations was higher than the single highest September daily maximum observed (1950–2014) for 5 out of 17 stations (∼30% of the stations). Ida-like extreme daily rain rates are projected to be, on average, more than 2 times more likely to occur at the end of the century in the simulations (with some regions as high as 5 times). This work demonstrates that integrating a high-resolution atmospheric model’s present-day and thermodynamically modified future simulations along with ground observations, within a nonstationary statistical framework, is crucial for understanding changing characteristics of extreme weather events. Significance Statement Daily scale extreme precipitation is expected to become more frequent and severe, as evidenced by observations and model simulations. While it is important to investigate how these intensifying heavy rainfall events affect current engineering standards, fewer studies have contextualized how warming impacts the most extreme rainfall from a single storm event relative to historical heavy downpours. In this study, we focused on the daily extreme rainfall associated with the extratropical transition of Hurricane Ida (2021), particularly over the northeastern United States—some of which exceeded the commonly used hydrologic design criteria for a 100-yr storm. Using a high-resolution atmospheric model simulation, we investigated how continued warming may influence the frequency of such daily rain rates. Under a high-emission scenario, these events are projected to become up to 5 times more likely at the end of the twenty-first century.

Dollan, Ishrat J↗

DOE OSTI2013

Collaborative Project. Understanding the effects of tides and eddies on the ocean dynamics, sea ice cover and decadal/centennial climate prediction using the Regional Arctic Climate Model (RACM)

The goal of this project is to develop an eddy resolving ocean model (POP) with tides coupled to a sea ice model (CICE) within the Regional Arctic System Model (RASM) to investigate the importance of ocean tides and mesoscale eddies in arctic climate simulations and quantify biases associated with these processes and how their relative contribution may improve decadal to centennial arctic climate predictions. Ocean, sea ice and coupled arctic climate response to these small scale processes will be evaluated with regard to their influence on mass, momentum and property exchange between oceans, shelf-basin, ice-ocean, and ocean-atmosphere. The project will facilitate the future routine inclusion of polar tides and eddies in Earth System Models when computing power allows. As such, the proposed research addresses the science in support of the BER’s Climate and Environmental Sciences Division Long Term Measure as it will improve the ocean and sea ice model components as well as the fully coupled RASM and Community Earth System Model (CESM) and it will make them more accurate and computationally efficient.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Report for Oregon State University Reporting Period: June 2016 to June 2017

The goal of this project is to develop an eddy resolving ocean model (POP) with tides coupled to a sea ice model (CICE) within the Regional Arctic System Model (RASM) to investigate the importance of ocean tides and mesoscale eddies in arctic climate simulations and quantify biases associated with these processes and how their relative contribution may improve decadal to centennial arctic climate predictions. Ocean, sea ice and coupled arctic climate response to these small scale processes will be evaluated with regard to their influence on mass, momentum and property exchange between oceans, shelf-basin, ice-ocean, and ocean-atmosphere. The project will facilitate the future routine inclusion of polar tides and eddies in Earth System Models when computing power allows. As such, the proposed research addresses the science in support of the BER’s Climate and Environmental Sciences Division Long Term Measure as it will improve the ocean and sea ice model components as well as the fully coupled RASM and Community Earth System Model (CESM) and it will make them more accurate and computationally efficient.

58 GEOSCIENCES↗

DOE OSTI2021

WORKSHOP ON URBAN SCALE PROCESSES AND THEIR REPRESENTATION IN HIGH SPATIAL RESOLUTION EARTH SYSTEM MODELS

It is essential that numerical models used to study physics, chemistry, and biology affecting the Earth system at regional and global scales represent the effects of urban areas on climate and the effects of changing the climate on urban areas. At the same time, it is essential to develop state of the art, simple and accurate urban models to better understand the relevant processes and also toaddress issues related to urban security against the spectra of chemical, biological and radiological (CBR) hazards. Towards bringing these communities together, a 2.5-day international workshop was held at Argonne National Laboratory (ANL) in the Chicago area on May 22-24, 2019. This workshop brought together national and international experts to develop a roadmap for a better understanding of the issues associated with urban areas and at enhancing the capabilities of regional and global Earth System models (ESMs) in representing the atmospheric dynamics and chemistry, unique aspects of the biosphere and land use, and human dimensions of the urban environment. This workshop was especially important to those developing very high-resolution versions of regional and global models. The workshop also discussed existing datasets, including in situ and satellite observations, and the emerging smart city sensing technologies and their possible use in model development (e.g., the NSF-funded Array of Things network currently operating in Chicago and expanding to other cities).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Sensitivity of Regional WRF‐Chem Air Quality and Weather Simulations to Biomass‐Burning Emission Data Sets: A Case Study of the Impact of Canadian Wildfire on the US°

This study focuses on the period from June 26 to 29, 2023, when record‐breaking Canadian wildfires severely impacted air quality in the Midwest United States. Using the Weather Research and Forecasting Model with Chemistry (WRF‐Chem) and four biomass‐burning data sets (Fire Inventory from NCAR version 1, Fire Inventory from NCAR version 2.5, Quick Fire Emissions Data set [QFED], and Regional ABI‐VIIRS Emission), we analyzed aerosol transport from Canada to the US and assessed the model's accuracy in predicting PM 2.5 , O 3 , CO and aerosol weather feedback. Model simulations were compared with ground‐based and remote sensing observations as well as field measurements from the Community Research on Climate and Urban Science (CROCUS) project. Our findings show that the movement of a low‐pressure system from the Great Lakes to the Atlantic, combined with the high‐pressure system over the Atlantic, caused the transport of aerosols from Canadian wildfires to the US. Results show WRF‐Chem significantly underestimated key atmospheric components: aerosol optical depth (AOD) by over 50%, PM 2.5 by 65%–90% and peak O 3 concentrations by 50%–55% across four biomass burning data sets. Additionally, CO and NO 2 concentrations were underpredicted. The substantial underestimation of PM 2.5 led to an overestimation of temperature by up to 3.6 °C primarily due to excessive downward shortwave radiation, which resulted from the underestimation of direct aerosol effects and an increase in sensible heat flux. Among the biomass‐burning data sets, QFED produced the most accurate AOD and PM 2.5 predictions due to improved wildfire emission estimates, leading to a 1.0 to 1.5 °C reduction in temperature overestimation during the daytime. These findings underscore the need for improving wildfire emission estimates for trace gases and aerosols to enhance air quality and weather feedback predictions.

WRF-chem model↗

DOE OSTI2020

Heavy and wet: The consequences of violating assumptions of measuring soil microbial growth efficiency using the 18O water method

Soils store more carbon than the biosphere and atmosphere combined, and the efficiency to which soil microorganisms allocate carbon to growth rather than respiration is increasingly considered a proxy for the soil capacity to store carbon. This carbon use efficiency (CUE) is measured via different methods, and more recently, the 18O-H2O method has been embraced as a significant improvement for measuring CUE of soil microbial communities. Based on extrapolating 18O incorporation into DNA to new biomass, this measurement makes various implicit assumptions about the microbial community at hand. Here we conducted a literature review to evaluate how viable these assumptions are and then developed a mathematical model to test how violating them affects estimates of the growth component of CUE in soil. We applied this model to previously collected data from two kinds of soil microbial communities. By changing one parameter at a time, we confirmed our previous observation that CUE was reduced by fungal removal. Our results also show that depending on the microbial community composition, there can be substantial discrepancies between estimated and true microbial growth. Of the numerous implicit assumptions that might be violated, not accounting for the contribution of sources of oxygen other than extracellular water to DNA leads to a consistent underestimation of CUE. We present a framework that allows researchers to evaluate how their experimental conditions may influence their 18O-H2O-based CUE measurements and suggest the parameters that need further constraining to more accurately quantify growth and CUE.

Environmental Sciences & Ecology↗

NASA NTRS1978

An experimental/analytical program to assess the utility of lidar for pollution monitoring

The development and demonstration of lidar techniques for the remote measurement of atmospheric constituents and transport processes in the lower troposphere was carried out. Particular emphasis was given to techniques for monitoring SO2 and particulates, the principal pollutants in power plant and industrial plumes. Data from a plume dispersion study conducted in Maryland during September and October 1976 were reduced, and a data base was assembled which is available to the scientific community for plume model verification. A UV Differential Absorption Lidar (DIAL) was built, and preliminary testing was done.

Mills, F. S.↗

NASA NTRS1999

Monitoring Global Geophysical Fluids by Space Geodesy

Since its establishment on 1/1/1998 by the International Earth Rotation Service, the Coordinating Center for Monitoring Global Geophysical Fluids (MGGF) and its seven Special Bureaus have engaged in an effort to support and facilitate the understanding of the geophysical fluids in global geodynamics research. Mass transports in the atmosphere-hydrosphere-solid Earth-core system (the "global geophysical fluids") will cause the following geodynamic effects on a broad time scale: (1) variations in the solid Earth's rotation (in length-of-day and polar motion/nutation) via the conservation of angular momentum and effected by torques at the fluid-solid Earth interface; (2) changes in the global gravitational field according to Newton's gravitational law; and (3) motion in the center of mass of the solid Earth relative to that of the whole Earth ("geocenter") via the conservation of linear momentum. These minute signals have become observable by space geodetic techniques, primarily VLBI, SLR, GPS, and DORIS, with ever increasing precision/accuracy and temporal/spatial resolution. Each of the seven Special Bureaus within MGGF is responsible for calculations related to a specific Earth component or aspect -- Atmosphere, Ocean, Hydrology, Ocean Tides, Mantle, Core, and Gravity/Geocenter. Angular momenta and torques, gravitational coefficients, and geocenter shift will be computed for geophysical fluids based on global observational data, and from state-of-the-art models, some of which assimilate such data. The computed quantities, algorithm and data formats are standardized. The results are archived and made available to the scientific research community. This paper reports the status of the MGGF activities and current results.

Chao, Benjamin F.↗

NASA NTRS2002

Building a virtual planet

The virtual Planetary Laboratory (VPL) is a recently funded 5-yr project, which seeks toimprove our understanding of the range of plausible environments and the likely signatures for life on extrasolar terrestrial planets. To achieve these goals we are developing a suite of innovative modeling tools to simulate the environments and spectra of extrasolar planets. The core of the VPL IS a coupled radiative transfer/climate/chemistry model, which is augmented by interchangeable modules which characterize geological, exogenic, atmospheric escape, and life processes. The VPL is validated using data derived from terrestrial planets within our own solar system. The VPL will be used to explore the plausible range of atmospheric composittions and globally averaged spectra for extrasolar planets and for early Earth, and will improve our understanding of the effect of life on a planet's atmospheric spectrum and composition. The models will also be used to create a comprehensive spectral catalog to provide recommendations on the optimum wavelength range, spectral resolution, and instrument sensitivity required to characterize extrasolar terrestrial planets. Although developed by our team, the VPL is envisioned to be a comprehensive and flexible tool, which can be collaboratively used by the broader planetary science and astrobiology communities. This presentation will describe the project concept, the tasks involved, and will outline current progress to date. This work is funded by the NASA Astrobiology Institute.

astrobiology↗

NASA NTRS2015

Improving Climate Projections Using "Intelligent" Ensembles

Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and that these metrics can be used to evaluate model quality in both current and future climate states. This information will be used to produce new consensus projections and provide communities with improved climate projections for urgent decision-making.

Baker, Noel C.↗

NASA NTRS2015

Improving Climate Projections Using "Intelligent" Ensembles

Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and that these metrics can be used to evaluate model quality in both current and future climate states. This information will be used to produce new consensus projections and provide communities with improved climate projections for urgent decision-making.

Baker, Noel C.↗

DOE OSTI2024

From peak to plummet: impending decline of the warm Arctic-cold continents phenomenon

Abstract This study assesses the projected trajectory of Warm Arctic-Cold Continent (WACC) events in East Asia and North America through large ensemble simulation for the upcoming decades. It analyses the evolution of the geographical boundaries of threshold cold temperatures, revealing a significant northward shift as a sign of global warming’s impact on the southward advancement of Arctic cold air. While validating the intensification of the WACC phenomenon until the 2020 s, echoing earlier studies, the findings indicate a marked decrease beginning in the 2030s. If warming is not curbed, this shift suggests a critical modification in the WACC pattern, prompting a re-evaluation of existing theories and models for extreme winter weather events. The results have major implications, spurring communities impacted by WACC to anticipate future changes and encouraging the climate forecasting community to update conceptual models for improved adaptation and mitigation approaches.

Meteorology & Atmospheric Sciences↗

NASA NTRSDate not supplied

Building Sustainable Capacity within Under-Represented Communities Through A Deep Partnership Model

Despite varied programmatic inducements and the documented benefits of Diversity Equity & Inclusion (DE&I), participation rates of underrepresented communities within NASA’s planetary sciences activities have remained low and nearly unchanged over the last decade. The lack of success of various efforts may be attributable to factors identified in social science research. First, the proportionality of under-represented groups has been shown to be critical to achieving the positive impacts of DE&I. When under-represented groups make up less than ~30%, group dynamics such as assimilation or tokenism routinely appear, with destructive and counter-productive results. Additionally, if participation only occurs within limited segments of an organization, benefits may be limited. Proportionality must extend across all levels or layers of the organization for the benefits of DE&I to accrue. Second, the inclusion of “Third Spaces” in the planning and support of DE&I efforts is critical to the long-term success or “stickiness” of DE&I activities. Third Spaces are those beyond home (First Space) and work (Second Space) where informal, community-building activities occur. Examples include conferences, after-work activities, and weekend social engagements. Without explicitly acknowledging and including “Third Space” interactions, DE&I efforts can fall short of their long-term goals. In 2014, the Laboratory for Atmospheric and Space Physics (LASP) at the University of Colorado Boulder began a partnership with the United Arab Emirates to develop and fly a space mission to Mars. The scientific mission had an explicit goal of training scientists and engineers, and creating a sustainable ecosystem that would spark and accelerate the UAE’s space economy. To accomplish this, LASP and the UAE set up a program that matched scientists and engineers in one-on-one mentorship relationships, at all levels of the organization. Over the course of the roughly 4-year project, those partnering relationships fostered not only strong professional relationships and knowledge transfer, but also personal friendships that extended into “Third Spaces.” The UAE/LASP partnership now continues through the co-development of an asteroid mission currently in definition phase. In collaboration with NASA Ames Research Center, LASP is developing the conceptual frame work to extend this deep partnership model to domestic opportunities. By implementing a planetary science mission that employs an analogous one-on-one partnership model across all elements of the organization, this project will demonstrate how proportionality and Third Space relationships can enable the development of localized, sustainable communities that are explicitly and deeply engaged with the NASA ecosystem.

Capacity Building↗