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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Causes and evolution of winter polynyas north of Greenland

During the 42-year period (1979–2020) of satellite measurements, four major winter (December–March) polynyas have been observed north of Greenland: one in December 1986 and three in the last decade, i.e., February of 2011, 2017, and 2018. The 2018 polynya was unparalleled in its magnitude and duration compared to the three previous events. Given the apparent recent increase in the occurrence of these extreme events, this study aims to examine their evolution and causality, in terms of forced versus natural variability. The limited weather station and remotely sensed sea ice data are analyzed combining with output from the fully coupled Regional Arctic System Model (RASM), including one hindcast and two ensemble simulations. We found that neither the accompanying anomalous warm surface air intrusion nor the ocean below had an impact (i.e., no significant ice melting) on the evolution of the observed winter open-water episodes in the region. Instead, the extreme atmospheric wind forcing resulted in greater sea ice deformation and transport offshore, accounting for the majority of sea ice loss in all four polynyas. Our analysis suggests that strong southerly winds (i.e., northward wind with speeds greater than 10 m s –1 ) blowing persistently over the study region for at least 2 d or more were required over the study region to mechanically redistribute some of the thickest Arctic sea ice out of the region and thus to create open-water areas (i.e., a latent heat polynya). To assess the role of internal variability versus external forcing of such events, we carried out and examined results from the two RASM ensembles dynamically downscaled with output from the Community Earth System Model (CESM) Decadal Prediction Large Ensemble (DPLE) simulations. Out of 100 winters in each of the two ensembles (initialized 30 years apart: one in December 1985 and another in December 2015), 17 and 16 winter polynyas were produced north of Greenland, respectively. The frequency of polynya occurrence had no apparent sensitivity to the initial sea ice thickness in the study area pointing to internal variability of atmospheric forcing as a dominant cause of winter polynyas north of Greenland. We assert that dynamical downscaling using a high-resolution regional climate model offers a robust tool for process-level examination in space and time, synthesis with limited observations, and probabilistic forecasts of Arctic events, such as the ones being investigated here and elsewhere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Precipitation Trade Wind Cumuli within EUREC 4 A Field Campaign Report

The campaign Trades Cumuli Precipitation Initiation and Characterization (TCPIC) within the overarching Elucidating the Role of Clouds-Circulation Coupling in Climate EUREC 4 A campaign took place from 17 January 2020 to 20 February 2020, a total of 35 days. The campaign complemented the more extensive EUREC 4 A campaign focusing on cumulus clouds' role in the Earth's climate. TCPIC concentrated on understanding what triggers the onset and development of precipitation in trade wind cumulus clouds. The campaign requested the deployment of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) roll, pitch, and heave (RPH) stabilization platform to stabilize two radars on the Maria S. Merian research vessel (RV). The advanced remote-sensing techniques from stabilized radars characterized the entire precipitation life cycle, from the formation of larger cloud drops to precipitation evaporating on its way to the surface. Retrievals of evaporation rates, to track how rain affects the trade wind boundary layer, will be based on the zenith-pointing Doppler observations collected from the stabilized micro rain radar (MRR). Figure 1 shows the instrumentation's deployment on the RV: we installed the AMF RPH stabilization platform and the radars on the uppermost deck (peil deck) of the ship. For installing the devices, we coordinated a test phase of the equipment on the Maria S. Merian RV from 25 to 29 October 2019 in Emden harbor, Germany. In this testing phase, we set up all the connections, tested how to mount the W-band and the micro rain radars firmly on the table, and experimented with guided movements of the table to test the resistance of the whole system. Figure 1 shows the final tests conducted in Emden with the stable platform and the radars mounted.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Doppler Lidar Motion-Correction (DLMC) Value-Added Product Report

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) second ARM Mobile Facility (AMF2) Doppler lidar (S/N 0319-160) was deployed on the German ice breaker Polarstern during the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign during 2019-2020 (see Figure 1). This was the first deployment of the new AMF2 Doppler lidar, as well as the first ship-based deployment of a Doppler lidar (DL) by ARM. In contrast to land-based deployments, the lidar’s heading (a.k.a. home point) and tilt are constantly changing, and lidar’s radial velocity measurements are impacted by the ship’s motion. Since the beam directions are reported relative to the instrument’s frame of reference, derivation of higher-order data products such as wind speed and direction require that the lidar’s attitude and translational velocity be properly accounted for. The Doppler Lidar Motion-Correction (DLMC) Value-Added-Product (VAP) was developed specifically for ship-based deployments of the Doppler lidar. This VAP combines raw uncorrected data from the DL and simultaneous measurements from the ARM Navigation system (NAV) (Walton 2019) to transform the beam angles from the lidar coordinate system to an Earth-fixed coordinate system. The VAP also removes the contribution of the lidar’s platform velocity from the radial velocity measurements. This report documents the methods used by the DLMC to perform these corrections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Atmospheric Variability Drives Anomalies in the Bering Sea Air–Sea Heat Exchange

Abstract High latitudes, including the Bering Sea, are experiencing unprecedented rates of change. Long-term Bering Sea warming trends have been identified, and marine heatwaves (MHWs), event-scale elevated sea surface temperature (SST) extremes, have also increased in frequency and longevity in recent years. Recent work has shown that variability in air–sea coupling plays a dominant role in driving Bering Sea upper-ocean thermal variability and that surface forcing has driven an increase in the occurrence of positive ocean temperature anomalies since 2010. In this work, we characterize the drivers of the anomalous surface air–sea heat fluxes in the Bering Sea over the period 2010–22 using ERA5 fields. We show that the surface turbulent heat flux dominates the net surface heat flux variability from September to April and is primarily a result of near-surface air temperature and specific humidity anomalies. The airmass anomalies that account for the majority of the turbulent heat flux variability are a function of wind direction, with southerly (northerly) wind advecting anomalously warm (cool), moist (dry) air over the Bering Sea, resulting in positive (negative) surface turbulent flux anomalies. During the remaining months of the year, anomalies in the surface radiative fluxes account for the majority of the net surface heat flux variability and are a result of anomalous cloud coverage, anomalous lower-tropospheric virtual temperature, and sea ice coverage variability. Our results indicate that atmospheric variability drives much of the Bering Sea upper-ocean temperature variability through the mediation of the surface heat fluxes during the analysis period. Significance Statement A long-term ocean warming trend and a recent increase in marine heatwaves in the Bering Sea have been identified. Previous work showed that anomalies in the exchange of heat between the ocean and the atmosphere were the primary driver of Bering Sea temperature variability, but the processes responsible for the heat exchange anomalies were unknown. In this work, we show that the atmosphere is the primary driver of anomalies in the Bering Sea air–sea heat exchange and therefore plays an important role in altering the thermal state of the Bering Sea. Our results highlight the importance of understanding more about how the ocean and the atmosphere interact at high latitudes and how this relationship will be affected by future climate change.

Hayden, Emily E. [a College of Earth, Ocean, and A↗
DOE OSTI2020

Wintertime Arctic Oscillation and North Atlantic Oscillation and their impacts on the Northern Hemisphere climate in E3SM

The characteristics of the wintertime Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) and their impacts on climate variability over the Northern Hemisphere are important metrics for evaluating a climate system model. Observational analyses reveal that the horizontal and vertical structures in the AO and NAO exhibit a meridional dipole and a large-scale barotropic pattern between the Arctic and mid-latitudes. Historical model simulations from the Energy Exascale Earth System Model (E3SM-HIST) are used to identify how well it captures these major climate modes. It is found that the simulated AO and NAO modes have spatial structures similar to the observed features. In addition, the observed frequency bands in the AO and NAO-related time variability are captured well in the E3SM-HIST simulation. Associated with the positive phase in wintertime AO and NAO, zonal flow and warm advection in mid-latitude continents are enhanced, along with stronger cold flow from enhanced northerly winds over high latitudes. These features are linked to the atmospheric circulation pattern reflected by lower SLP anomalies over the Arctic and higher SLP anomalies over the mid-latitudes. In E3SM-HIST, these spatial associations and main structural features are analogous to those in observations. In the time-height evolution related to winter AO and NAO modes, it can also be seen that the simulations reproduce the downward propagating patterns in observations. Nevertheless, the vertical structures associated with AO and NAO in E3SM-HIST exhibit substantial biases in the lower stratosphere. The cause of these stratospheric biases is investigated using the strength of climatological stratospheric polar vortex (SPV) and wave activity fluxes. The results herein suggest that E3SM-HIST has a reasonable skill in reproducing the observed characteristics related to the winter AO and NAO, although there exist systematic biases in the associated climate variability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Fast Response of East Asian Precipitation in June 2020 to Local and Remote Aerosol Emission Reductions during COVID-19

Here, in this study, the fast response of East Asian summer precipitation to COVID-19–induced aerosol emission reductions is examined using the Community Earth System Model, version 2.2 (CESM2.2). The emission reductions decreased aerosol optical depth and cloud cover over northern China in June 2020. The troposphere became warmer, strengthening the land–sea thermal contrast and anomalous southerly winds. The subtropical westerly jet accelerated and shifted southward, favoring low-level convergence, upward air motions, and subsequent condensational heating over the Yangtze River basin (YRB). The feedback of condensational heating in return strengthened the convergence and ascent. The western North Pacific subtropical high was intensified, which further enhanced the moisture advection and convergence over the YRB. Both the enhanced moisture convergence and ascent increased precipitation over the YRB during June 2020. Furthermore, local and remote emission reductions show different impacts on convection and moisture transport over the YRB. The emission reductions over China caused stronger convective precipitation (1.15 vs 0.63 mm day −1 ) but weaker larger-scale precipitation (1.17 vs 2.24 mm day −1 ) than the emission reductions outside China. In addition to the emission reductions, the sea surface temperature (SST) anomalies in 2020 also play an important role in increasing precipitation over the YRB, contributing about 42.8%. The relative contribution of SST anomalies also increases under the COVID-19–induced emission scenario.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Air-sea interactions yielding rapid Beaufort Sea ice losses during the 2021 ONR THINICE Pilot Field Campaign

Seasonal sea ice coverage has declined in the Pacific Arctic region. Losses of the ice cover have modified the region’s surface heat and momentum fluxes providing weather systems more direct interaction with the upper ocean. For example, recent cyclones that have passed over these waters have initiated multiple air-sea interactions and have impacted mixed layer depth, wave properties, and sea ice mass budgets due to diabatic and/or advective processes. As a United States Office of Naval Research (ONR) Departmental Research initiative, one key component of the ONR THINICE program was to advance knowledge on Arctic cyclone coupling with the ocean surface, its ice cover, and understand how such coupling can lead to rapid ice loss. Leading up to the primary field campaign in August 2022, a pilot field campaign from 19 August to 13 September 2021 focused in Utqiagvik, Alaska and Longyearbyen, Svalbard was carried out. This period was marked by frequent Arctic cyclones, periods of strong low-level winds, and stints of extreme short-term Beaufort Sea ice area losses. Cyclones traversed these waters much more frequently than usual during this 26-day period, but did not exhibit extreme central pressures indicative of high intensity and impactful storms. Using ERA5 atmospheric reanalysis fields, CERES and AIRS surface flux retrievals, and in situ sensor data collected from ice-tethered profilers and ice mass balance buoys, we highlight air-sea-ice interactions in the Beaufort Sea during and between these cyclones leading up to extreme ice loss events. Our case study analysis is aimed at understanding how Arctic cyclones, including air-sea interactions prompted by their passage over the marginal ice zone, influence the end-of-summer ice conditions and ice loss events. This study provides an example where frequent, yet weak storms drive rather large marginal sea-scale losses albeit with heterogenous sea ice effects at local scales.

Ballinger, Thomas [International Arctic Research C↗
DOE OSTI2021

Southwest Pacific tropical cyclone development classification utilizing machine learning and synoptic composites

This study evaluates the ability of machine learning algorithms to classify tropical depressions (TDs) and tropical storms (TSs) in the western region of the southwest Pacific Ocean (SWPO). Decision rules are generated to predict the environment required for a depression to fully develop into a mature storm, and the most influential predictors in the classification decision are ranked. TD and TS are discriminated based on a maximum sustained wind speed threshold (≥17 ms -1 ). Various aerosol, thermodynamic, and dynamic parameters are extracted closest to the initiation point of each non-developing and developing sample. The covariates associated with each labelled sample are used to train a decision tree and random forest model. Results using a testing dataset suggest the random forest approach more accurately distinguishes between non-developing and developing samples. The classification accuracy of the decision tree and random forest are 72% and 91%, respectively. Random forest outperformed the decision tree by providing higher accuracy in test data. The most important variables for binary classification are sea salt aerosol optical depth (AOD), 1,000 mb relative humidity, and sea surface temperature. AOD is a quantitative estimate of the aerosols presents in the air through the extinction of a ray of light as it passes through the atmosphere. Mean composite maps constructed in an unsupervised manner have been created for the most important variables identified by the random forest classifier during TD and TS events to highlight the difference in geophysical and aerosol variables' climatology during the two different classifications. This work will advance the risk management strategies for northeastern Australia and other SWPO basin islands to control their tropical cyclone related losses through prioritizing forecasting variables that are the strongest predictors of the strengthening of tropical depressions into tropical cyclones.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Quantifying the Impact of Vertical Resolution on the Representation of Marine Boundary Layer Physics for Global-Scale Models

Abstract While GCM horizontal resolution has received the majority of scale improvements in recent years, ample evidence suggests that a model’s vertical resolution exerts a strong control on its ability to accurately simulate the physics of the marine boundary layer. Here we show that, regardless of parameter tuning, the ability of a single-column model (SCM) to simulate the subtropical marine boundary layer improves when its vertical resolution is improved. We introduce a novel objective tuning technique to optimize the parameters of an SCM against profiles of temperature and moisture and their turbulent fluxes, horizontal winds, cloud water, and rainwater from large-eddy simulations (LES). We use this method to identify optimal parameters for simulating marine stratocumulus and shallow cumulus. The novel tuning method utilizes an objective performance metric that accounts for the uncertainty in the LES output, including the covariability between model variables. Optimization is performed independently for different vertical grid spacings and value of time step, ranging from coarse scales often used in current global models (120 m, 180 s) to fine scales often used in parameterization development and large-eddy simulations (10 m, 15 s). Uncertainty-weighted disagreement between the SCM and LES decreases by a factor of ∼5 when vertical grid spacing is improved from 120 to 10 m, with time step reductions being of secondary importance. Model performance is shown to converge at a vertical grid spacing of 20 m, with further refinements to 10 m leading to little further improvement. Significance Statement In successive generations of computer models that simulate Earth’s atmosphere, improvements have been mainly accomplished by reducing the horizontal sizes of discretized grid boxes, while the vertical grid spacing has seen comparatively lesser refinements. Here we advocate for additional attention to be paid to the number of vertical layers in these models, especially in the model layers closest to Earth’s surface where climatologically important marine stratocumulus and shallow cumulus clouds reside. Our experiments show that the ability of a one-dimensional model to represent physical processes important to these clouds is strongly dependent on the model’s vertical grid spacing.

Meteorology & Atmospheric Sciences↗
DOE OSTI2024

Characterizing Ice Nucleating Particles Over the Southern Ocean Using Simultaneous Aircraft and Ship Observations

Abstract Supercooled liquid clouds are ubiquitous over the Southern Ocean (SO), even to temperatures below −20°C, and comprise a large fraction of the marine boundary layer (MBL) clouds. Earth system models and reanalysis products have struggled to reproduce the observed cloud phase distribution and occurrence of cloud ice in the region. Recent simulations found the microphysical representation of ice nucleation and growth has a large impact on these properties, however, measurements of SO ice nucleating particles (INPs) to validate simulations are sparse. This study presents measurements of INPs from simultaneous aircraft and ship campaigns conducted over the SO in austral summer 2018, which include the first in situ observations in and above cloud in the region. Our results confirm recent observations that INP concentrations are uniformly lower than measurements made in the late 1960s. While INP concentrations below and above cloud are similar, higher ice nucleation efficiency above cloud supports model simulations that the dominant INP composition varies with height. Model parameterizations based solely on aerosol properties capture the mean relationship between INP concentration and temperature but not the observed variability, which is likely related to the only modest correlations observed between INPs and environmental or aerosol metrics. Including wind speed in addition to activation temperature in a marine INP parameterization reduces bias but does not explain the large range of observed INP concentrations. Direct and indirect inference of marine INP size suggests MBL INPs, at least during Austral summer, are dominated by particles with diameters smaller than 500 nm.

Meteorology & Atmospheric Sciences↗
DOE OSTI2020

Observations for Model Intercomparison Project (Obs4MIPs): status for CMIP6

The Observations for Model Intercomparison Project (Obs4MIPs) was initiated in 2010 to facilitate the use of observations in climate model evaluation and research, with a particular target being the Coupled Model Intercomparison Project (CMIP), a major initiative of the World Climate Research Programme (WCRP). To this end, Obs4MIPs (1) targets observed variables that can be compared to CMIP model variables; (2) utilizes dataset formatting specifications and metadata requirements closely aligned with CMIP model output; (3) provides brief technical documentation for each dataset, designed for nonexperts and tailored towards relevance for model evaluation, including information on uncertainty, dataset merits, and limitations; and (4) disseminates the data through the Earth System Grid Federation (ESGF) platforms, making the observations searchable and accessible via the same portals as the model output. Taken together, these characteristics of the organization and structure of obs4MIPs should entice a more diverse community of researchers to engage in the comparison of model output with observations and to contribute to a more comprehensive evaluation of the climate models. At present, the number of obs4MIPs datasets has grown to about 80; many are undergoing updates, with another 20 or so in preparation, and more than 100 are proposed and under consideration. A partial list of current global satellite-based datasets includes humidity and temperature profiles; a wide range of cloud and aerosol observations; ocean surface wind, temperature, height, and sea ice fraction; surface and top-of-atmosphere longwave and shortwave radiation; and ozone (O 3 ), methane (CH 4 ), and carbon dioxide (CO 2 ) products. A partial list of proposed products expected to be useful in analyzing CMIP6 results includes the following: alternative products for the above quantities, additional products for ocean surface flux and chlorophyll products, a number of vegetation products (e.g., FAPAR, LAI, burned area fraction), ice sheet mass and height, carbon monoxide (CO), and nitrogen dioxide (NO 2 ). While most existing obs4MIPs datasets consist of monthly-mean gridded data over the global domain, products with higher time resolution (e.g., daily) and/or regional products are now receiving more attention. Along with an increasing number of datasets, obs4MIPs has implemented a number of capability upgrades including (1) an updated obs4MIPs data specifications document that provides additional search facets and generally improves congruence with CMIP6 specifications for model datasets, (2) a set of six easily understood indicators that help guide users as to a dataset's maturity and suitability for application, and (3) an option to supply supplemental information about a dataset beyond what can be found in the standard metadata. With the maturation of the obs4MIPs framework, the dataset inclusion process, and the dataset formatting guidelines and resources, the scope of the observations being considered is expected to grow to include gridded in situ datasets as well as datasets with a regional focus, and the ultimate intent is to judiciously expand this scope to any observation dataset that has applicability for evaluation of the types of Earth system models used in CMIP.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Role of the Terrestrial Biosphere in Atmospheric Chemistry and Climate

The terrestrial biosphere–atmosphere interface provides a key chemical, biological, and physical lower boundary for the atmosphere. The presence of vegetation itself modifies the physical boundary, or the biogeophysical aspects of the system, by controlling important climate drivers such as soil moisture, light environment, and temperature. The leaf surface area of the terrestrial biosphere provides additional surface area for emissions, and it can be up to 55% of the total Earth’s surface area during the boreal summer. Vegetation also influences the biogeochemical aspects of the system by emitting a broad suite of reactive trace gases such as biogenic volatile organic compound (BVOC) emissions and climate-relevant primary biological aerosol particles (PBAP). Many of these emissions are a function of meteorological and climatological conditions at the surface, including temperature, light environment, soil moisture, and winds. Once emitted, they can be processed in the troposphere through a suite of chemical reactions. BVOC can contribute to the formation of ozone and secondary organic aerosols (SOA), and PBAP can rupture to form smaller particles with climatic relevance. These emissions and subsequent aerosol products can influence atmospheric processes that affect the surface climate, such as the attenuation of radiation, the formation of greenhouse gases such as ozone that can feedback to surface air temperature, and the alteration of clouds and subsequent precipitation. These atmospheric changes can then feedback to the land surface and emissions themselves, creating positive or negative feedback loops that can dampen or amplify the emission response. For the dominant BVOC isoprene, the feedback response to temperature can be positive or negative depending on ambient temperatures that drive isoprene emissions. The feedback response to soil moisture and precipitation can be positive, negative, or uncoupled depending on the moisture content of the soil and the total atmospheric aerosol loading. For light, the isoprene response can be positive or negative depending on the role of diffuse light. Overall, these feedbacks highlight the dynamical response of the biosphere to changing atmospheric conditions across a range of time scales, from minutes for trace gases and aerosols, to months for phenological changes, to years for land cover and land use change. Here, the dynamic aspect of this system requires us to understand, simulate, and predict the complex feedbacks between the biosphere and atmosphere and understand their role in the simulation and understanding of climate and global change. From the observational perspective, these feedbacks are challenging to identify in observations, and predictive modeling tools provide a crucial link for understanding how these feedbacks will change under warming climate scenarios.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Projecting Future Energy Production from Operating Wind Farms in North America. Part I: Dynamical Downscaling

Abstract New simulations at 12-km grid spacing with the Weather and Research Forecasting (WRF) Model nested in the MPI Earth System Model (ESM) are used to quantify possible changes in wind power generation potential as a result of global warming. Annual capacity factors (CF; measures of electrical power production) computed by applying a power curve to hourly wind speeds at wind turbine hub height from this simulation are also used to illustrate the pitfalls in seeking to infer changes in wind power generation directly from low-spatial-resolution and time-averaged ESM output. WRF-derived CF are evaluated using observed daily CF from operating wind farms. The spatial correlation coefficient between modeled and observed mean CF is 0.65, and the root-mean-square error is 5.4 percentage points. Output from the MPI-WRF Model chain also captures some of the seasonal variability and the probability distribution of daily CF at operating wind farms. Projections of mean annual CF (CF A ) indicate no change to 2050 in the southern Great Plains and Northeast. Interannual variability of CF A increases in the Midwest, and CF A declines by up to 2 percentage points in the northern Great Plains. The probability of wind droughts (extended periods with anomalously low production) and wind bonus periods (high production) remains unchanged over most of the eastern United States. The probability of wind bonus periods exhibits some evidence of higher values over the Midwest in the 2040s, whereas the converse is true over the northern Great Plains. Significance Statement Wind energy is playing an increasingly important role in low-carbon-emission electricity generation. It is a “weather dependent” renewable energy source, and thus changes in the global atmosphere may cause changes in regional wind power production (PP) potential. We use PP data from operating wind farms to demonstrate that regional simulations exhibit skill in capturing actual power production. Projections to the middle of this century indicate that over most of North America east of the Rocky Mountains annual expected PP is largely unchanged, as is the probability of extended periods of anomalously high or low production. Any small declines in annual PP are of much smaller magnitude than changes due to technological innovation over the last two decades.

Meteorology & Atmospheric Sciences↗
DOE OSTI2025

Mesoscale Cellular Convection Detection and Classification Using Convolutional Neural Networks: Insights From Long-Term Observations at ARM Eastern North Atlantic Site

Marine boundary layer clouds are crucial in Earth's climate system. They frequently manifest as closed or open cell mesoscale cellular convection (MCC). MCC clouds are challenging to represent accurately in current climate models, highlighting the need for detailed observational data sets and in-depth analyses. This study utilizes over 8 years of observations from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility Eastern North Atlantic (ENA) site at Graciosa Island, Azores, to investigate these clouds. We first apply a convolutional neural network with a U-Net architecture to classify open and closed cells, marking the first application of such an approach for automatically detecting MCC patterns from ground-based radar measurements. This method addresses some observational gaps in satellite data related to low temporal resolution, nighttime challenges, and limited vertical structure capture. The analysis of the MCC cases shows clear differences between closed and open MCCs: Closed MCC clouds are characterized by lower cloud tops and bases, shallower cloud geometrical depth, weaker horizontal wind speeds, stronger atmospheric stability, and a more homogeneous liquid water path than open MCCs. Finally, we demonstrate two potential applications of our radar-based MCC classifications: (a) facilitating the investigation of aerosol-cloud interactions and (b) exploring meteorological factors along with MCC's evolution by integrating satellite imagery and back-trajectory analysis. The identified MCC cases offer a valuable resource for the scientific community to study MCC processes further and improve climate model accuracy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Shallow Cumulus Properties as Captured by Adiabatic Fraction in High-Resolution LES Simulations

Abstract Shallow convective clouds are important players in Earth’s energy budget and hydrological cycle, and are abundant in the tropical and subtropical belts. They greatly contribute to the uncertainty in climate predictions due to their unresolved, complex processes that include coupling between the dynamics and microphysics. Analysis of cloud structure can be simplified by considering cloud motions as a combination of moist adiabatic motions like adiabatic updrafts and turbulent motions leading to deviation from adiabaticity. In this work, we study the sizes and occurrence of adiabatic regions in shallow cumulus clouds during their growth and mature stages, and use the adiabatic fraction (AF) as a continuous metric to describe cloud processes and properties from the core to the edge. To do so, we simulate isolated trade wind cumulus clouds of different sizes using the System of Atmospheric Modeling (SAM) model in high resolution (10 m) with the Hebrew University spectral bin microphysics (SBM). The fine features in the clouds’ dynamics and microphysics, including small near-adiabatic volumes and a thin transition zone at the edge of the cloud (∼20–40 m in width), are captured. The AF is shown to be an efficient measure for analyzing cloud properties and key processes determining the droplet-size distribution formation and shape during the cloud evolution. Physical processes governing the properties of droplet size distributions at different cloud regions (e.g., core, edge) are analyzed in relation to AF. Significance Statement 1) This study investigates the evolution of cumulus clouds (Cu) using a 10-m-resolution LES model with spectral bin microphysics. 2) The study improves the understanding of the mutual effects of adiabatic updrafts and lateral entrainment and mixing. 3) The study demonstrates the existence of an adiabatic core in nonprecipitating Cu. 4) Shapes of the droplet size distributions are closely related to the adiabatic fraction values. 5) Utilization of high resolution reveals the existence of physically significant small features in the cloud structure, such as a narrow cloud interface zone and small adiabatic volumes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A multi-year short-range hindcast experiment with CESM1 for evaluating climate model moist processes from diurnal to interannual timescales

Abstract. We present a multi-year short-range hindcast experiment and its experimental design for better evaluation of both the mean state and variability of atmospheric moist processes in climate models from diurnal to interannual timescales and facilitate model development. We used the Community Earth System Model version 1 as the base model and performed a suite of 3 d hindcasts initialized every day starting at 00:00 Z from 1997 to 2012. Three processes – the diurnal cycle of clouds during different cloud regimes over the central US, precipitation and diabatic heating associated with the Madden–Julian Oscillation (MJO), and the response of precipitation, surface radiative and heat fluxes, as well as zonal wind stress to sea surface temperature anomalies associated with the El Niño–Southern Oscillation – are evaluated as examples to demonstrate how one can better utilize simulations from this experiment to gain insights into model errors and their connection to physical parameterizations or large-scale state. This is achieved by comparing the hindcasts with corresponding long-term observations for periods based on different phenomena. These analyses can only be done through this multi-year hindcast approach to establish robust statistics of the processes under well-controlled large-scale environment because these phenomena are either a result of interannual climate variability or only happen a few times in a given year (e.g., MJO, or cloud regime types). Furthermore, comparison of hindcasts to the typical simulations in climate mode with the same model allows one to infer what portion of a model's climate error directly comes from fast errors in the parameterizations of moist processes. As demonstrated here, model biases in the mean state and variability associated with parameterized moist processes usually develop within a few days and manifest within weeks to affect the simulations of large-scale circulation and ultimately the climate mean state and variability. Therefore, model developers can achieve additional useful understanding of the underlying problems in model physics by conducting a multi-year hindcast experiment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Data for "Land-based Resources for Engineered Carbon Dioxide Removal in the United States Exceed the Expected Needs"

Gigatonne-scale atmospheric carbon dioxide removal (CDR), alongside deep emission cuts, is critical to stabilizing the climate. However, some of the most scalable CDR technologies are also the most land intensive. Here, we examine whether adequate land resources exist in the contiguous United States to meet CDR targets when prioritizing grid emissions reduction, food production, and the protection of sensitive ecosystems. We focus on biomass carbon removal and storage (BiCRS) and direct air capture and storage (DACS) and show that suitable lands exceed the expected needs: 37.6 million hectares of land are available for BiCRS, resulting in 0.26 GtCO2 of CDR/year, and 34 million hectares are suitable for wind- and solar-powered DACS, resulting in 4.8 GtCO2 of CDR/year if facilities are co-located with geologic CO2 storage. We identify biomass and energy supply hotspots to meet CDR targets while ensuring land protection and minimizing land competition.

carbon↗
DOE OSTI2022

On the additivity of climate responses to the volcanic and solar forcing in the early 19th century

The early 19th century was the coldest period over the past 500 years, when strong tropical volcanic events and a solar minimum coincided. The 1809 unidentified eruption and the 1815 Tambora eruption happened consecutively during the Dalton minimum of solar irradiance; however, the relative role of the two forcing (volcano and solar) agents is still unclear. In this study, we examine the responses from a set of early 19th century simulations with combined and separated volcanic and solar forcing agents, as suggested in the protocol for the past1000 experiment of the Paleoclimate Modelling Intercomparison Project – Phase 4 (PMIP4). From 20-member ensemble simulations with the Max Planck Institute Earth system model (MPI-ESM1.2-LR), we find that the volcano- and solar-induced surface cooling is additive in the global mean/large scale, regardless of combining or separating the forcing agents. The two solar reconstructions (SATIRE (Spectral and Total Irradiance REconstruction-Millennia model) and PMOD (Physikalisch-Meteorologisches Observatorium Davos)) contribute to a cooling before and after 1815 of ~0.05 and ~0.15 K monthly average near-surface air cooling, respectively, indicating a limited solar contribution to the early 19th century cold period. The volcanic events provide the main cooling contributions, inducing a surface cooling that peaks at ~0.82 K for the 1809 event and ~1.35 K for Tambora. After the Tambora eruption, the temperature in most regions increases toward climatology largely within 5 years, along with the reduction of volcanic forcing. In the northern extratropical oceans, the temperature increases slowly at a constant rate until 1830, which is related to the reduction of seasonality and the concurrent changes in Arctic sea-ice extent. The albedo feedback of Arctic sea ice is found to be the main contributor to the Arctic amplification of the cooling signal. Several non-additive responses to solar and volcanic forcing happen on regional scales. In the atmosphere, the stratospheric polar vortex tends to strengthen when combining both volcano and solar forcing, even though the two forcing agents separately induce opposite-sign changes in stratospheric temperatures and zonal winds. In the ocean, when combining the two forcings, additional surface cold water propagates to the northern extratropics from the additional solar cooling in the tropics, which results in regional cooling along the propagation. Overall, this study not only quantifies the surface responses from combinations of the volcano and solar forcing, but also highlights the components that cannot be simply added from the responses of the individual forcing agents, indicating that a relatively small forcing agent (such as solar in early 19th century) can impact the response from the large forcing (such as the 1815 Tambora eruption) when considering regional climates.

54 ENVIRONMENTAL SCIENCES↗