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NASA NTRS2018

Reconstruction of Snow on Arctic Sea Ice

Snow on Arctic sea ice is a poorly observed variable that plays an important role in the Arctic climate system and impacts the remote sensing systems that monitor Arctic sea ice. We present and validate a reconstruction of Arctic snow depth based on observed sea ice motion and snowfall derived from reanalysis data. Overall, the reconstruction is in good agreement with direct measurements of snow depth from Operation IceBridge, slightly underestimating mean IceBridge snow depth. At the local scale (10 km), the reconstruction is more skilled than a weighted climatology over first year ice, but underestimates deeper snow over multiyear ice. Reconstructions of single buoy snow depths are unskilled, but the reconstruction shows skill in simulating the mean snow depth across all buoys. Spring snow depths show a lowtohigh crossArctic gradient and tend to be greatest in the Atlantic sector of the eastern Arctic. The relationship between ice type (multiyear or firstyear ice) and snow depth previously documented in the western Arctic is not evident in the eastern Arctic. Using ice type to weight snow depths for satellite ice thickness retrievals may not be justifiable in the eastern Arctic. Reconstructed snow depth across the Arctic shows significant interannual variability, suggesting that use of a fixed snow depth climatology may lead to biases in retrieved ice thickness and its variability. However, interannual variability in panArctic mean snow depth is comparable or smaller than the uncertainty in both the reconstruction and IceBridge, highlighting the need for high accuracy snow depth products and reconstructions.

sea ice↗

NASA NTRS2017

Bimodal SLD Ice Accretion on a NACA 0012 Airfoil Model

An initial ice shape database has been created to document ice accretions on a 21-inch chord NACA 0012 airfoil model resulting from an exposure to a Supercooled Large Droplet (SLD) icing cloud with a bimodal droplet distribution. The ice shapes created were documented with photographs, laser scanned surface measurements over a section of the model span, and measurement of the ice mass over the same section of each accretion. The icing conditions used in the test matrix were based upon previously measured ice shapes on the same model to connect the current database to previously measured information. Ice shapes resulting from the bimodal distribution as well as from equivalent standard droplet distributions were obtained and compared. Results indicate that the ice shapes resulting from the bimodal droplet distributions had higher mass and volume values than their standard distribution equivalents as well as having icing limits that extended further back on the chord of the model.

aircraft icing↗

NASA NTRS2019

initMIP-Antarctica: an Ice Sheet Model Initialization Experiment of ISMIP6

Ice sheet numerical modeling is an important tool to estimate the dynamic contribution of the Antarctic ice sheet to sea level rise over the coming centuries. The influence of initial conditions on ice sheet model simulations, however, is still unclear. To better understand this influence, an initial state intercomparison exercise (initMIP) has been developed to compare, evaluate, and improve initialization procedures and estimate their impact on century-scale simulations. initMIP is the first set of experiments of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6), which is the primary Coupled Model Intercomparison Project Phase 6 (CMIP6) activity focusing on the Greenland and Antarctic ice sheets. Following initMIP-Greenland, initMIP-Antarctica has been designed to explore uncertainties associated with model initialization and spin-up and to evaluate the impact of changes in external forcings. Starting from the state of the Antarctic ice sheet at the end of the initialization procedure, three forward experiments are each run for 100 years: a control run, a run with a surface mass balance anomaly, and a run with a basal melting anomaly beneath floating ice. This study presents the results of initMIP-Antarctica from 25 simulations performed by 16 international modeling groups. The submitted results use different initial conditions and initialization methods, as well as ice flow model parameters and reference external forcings. We find a good agreement among model responses to the surface mass balance anomaly but large variations in responses to the basal melting anomaly. These variations can be attributed to differences in the extent of ice shelves and their upstream tributaries, the numerical treatment of grounding line, and the initial ocean conditions applied, suggesting that ongoing efforts to better represent ice shelves in continental-scale models should continue.

ice sheet model↗

NASA NTRS2019

An Investigation into the Grain Structure of Impact Ice

To design effective anti-icing and de-icing technology for aircraft, scientists and engineers must obtain a fundamental understanding of the microstructural characteristics of impact ice. This study investigates the effects of icing parameters, such as airspeed and liquid water content (LWC), on impact ice microstructure near the interface to a metal substrate. Ice samples were accreted in the NASA Glenn Icing Research Tunnel and tested in the NASA Revolutionary Icing Materials Evaluation Laboratory. A microtome was used to shave down the ice to a thickness of < 1 mm for examination under a microscope. Samples were imaged at multiple magnifications using bright field imaging. The average grain size was determined for each sample in accordance with ASTM standard methods, and relationships between airspeed, LWC, and grain size were identified. It was observed that the average grain area in a given cross-section was linearly related to the distance of the cross-section from the metal surface. Finally, the effects of annealing and sublimation on the microstructure were also explored. Results show significant variation in the grain structure, suggesting a means by which icing condition influences adhesion strength.

grain↗

NASA NTRSDate not supplied

Bimodal SLD Ice Accretion on Swept NACA 0012 Airfoil Models

An ice shape database has been created to document ice accretions on a swept 15-inch chord NACA0012 model and a swept 36-inch chord NACA0012 airfoil model resulting from an exposure to a Supercooled Large Drop (SLD) icing cloud with a bimodal drop size distribution. The ice shapes created were documented with photographs, laser scanned surface measurements over a section of the model span, and measurement of the ice mass over the same section of each accretion. The icing conditions were based on a series of reference conditions that were previously used to generate ice shapes on these models. Drop distribution effects were evaluated by using the same IRT icing conditions except with either monomodal or bimodal drop distributions. Ice shapes resulting from the bimodal distribution as well as from equivalent monomodal drop size distributions were obtained and compared. Results indicate that the ice shapes and mass values from the monomodal and bimodal drop size distributions were the same within the range of repeatability for the conditions tested in this campaign.

Icing↗

NASA NTRSDate not supplied

The Measurement of Shear Strain in Impact Ice Using a Modified Lap Joint Test and Digital Image Correlation

The results of ice adhesion testing efforts are typically quantified using the maximum shear stress sustained at the interface before the ice detaches from the underlying substrate. While this singular value can be useful for understanding the role icing wind tunnel conditions and substrate surface properties have on the strength of the ice-substrate interface, it does not capture the mechanical behavior of the ice during an experiment. To better understand the deformation of the ice sample and ice-substrate interface during testing, digital image correlation was applied to the lap-joint shear test methodology utilized at NASA Glenn Research Center. Preparation of the sample surface for digital image correlation, initial parsing of the correlation data, and the time synchronization of data from multiple sources are discussed. Using the directional components of deformation measured via digital image correlation, a novel approach to calculating the interfacial shear strain is presented. Results from analyzing several impact ice samples consistently reveals a non-linear response in the ice during mechanical loading which occurs prior to sample delamination, a behavior not observable in the force and displacement data gathered from the testing apparatus. Both the full and small angle forms of the engineering shear strain are evaluated, with the full shear strain form providing considerably lower noise levels. The transition of sample response from near the interface to the bulk behavior of the ice under shear loading is discussed with results from several samples being presented.

Ice adhesion↗

NASA NTRSDate not supplied

The Measurement of Shear Strain in Impact Ice Using a Modified Lap Joint Test and Digital Image Correlation

: Ice Adhesion, Digital Image Correlation, Experim↗

NASA NTRS2022

Impact of the Arctic Oscillation from March on summertime sea ice

Current understanding of the cold season Arctic oscillation (AO) impact on the summertime sea ice is revisited in this study by analyzing the role from each month. Earlier studies examined the prolonged AO impact using a smooth average over 1–2 seasons (e.g. December–March, December–April, March–May), ignoring large month-to-month AO variability. This study finds that the March AO is most influential on the summertime sea ice loss. First, the March AO is most highly negative-correlated with the AO in summer. Secondly, surface energy budget, sea level pressure, and low-tropospheric circulation exhibit that their time-lagged responses to the positive (negative) phase of the March AO grow with time, transitioning to the patterns associated with the negative (positive) phase of the AO that induces sea ice decrease (increase) in summer. Time evolution of the surface energy budget explains the growth of the sea ice concentration anomaly in summer, and a warming-to-cooling transition in October. The regional difference in sea ice anomaly distribution can be also explained by circulation and surface energy budget patterns. The sea ice concentration along the pan-Arctic including the Laptev, East Siberian, Chukchi, and Beaufort Sea decreases (increases) in summer in response to the positive (negative) phase of the March AO, while the sea ice to the northeast of Greenland increases (decreases). This sea ice response is better represented by the March AO than by the seasonally averaged winter AO, suggesting that the March AO can play more significant role. This study also finds that the sea ice decrease in response to the positive AO is distinctively smaller in the 20th century than in the 21st century, along with the opposite sea ice response over the Canada Basin due to circulation difference between the two periods.

Arctic Oscillation↗

NASA NTRS2023

Importance of Atmospheric Feedbacks in Simulating the Seasonal Cycle of the Antarctic Sea Ice and Its Response to Perturbations

The seasonal cycle of the Antarctic sea ice extent is largely controlled by the evolution of the insolation received at the top of the atmosphere. However, sea ice processes and feedbacks with the ocean and the atmosphere can modulate this seasonal cycle. Here, the atmospheric feedbacks are quantified in a series of idealized sensitivity experiments performed with an eddy-permitting (1/4°) NEMO-LIM3 Southern Ocean configuration, including a representation of ice shelf cavities, in which the model was either driven by an atmospheric reanalysis or coupled to the COSMO-CLM 2 regional atmospheric model. In these experiments, sea ice thermodynamics and dynamics as well as the exchanges with the ocean and atmosphere are strongly perturbed. This perturbation is achieved by modifying snow and ice thermal conductivities, the vertical mixing in the ocean top layers, the effect of freshwater uptake/release upon sea ice growth/melt, ice dynamics and surface albedo. We show that the changes in surface heat fluxes are very different between the configurations driven by the reanalysis and those coupled to the atmosphere. Atmospheric feedbacks enhance the response of the modelled winter ice extent to any of the perturbed processes, and the enhancement is strongest when the albedo is modified. The response of sea ice volume and extent to changes in entrainment of subsurface warm waters to the ocean surface is also greatly amplified by the coupling with the atmosphere. By contrast, the atmospheric feedbacks can damp the impact of the perturbations affecting the heat conductivity through sea ice.

Atmospheric feedbacks↗

DOE OSTI2020

Effect of pH on the Activity of Ice-Binding Protein from Marinomonas primoryensis

The ability of an ice-binding protein (IBP) from Marinomonas primoryensis (MpIBP) to influence ice crystal growth and structure in nonphysiological pH environments was investigated in this work. The ability for MpIBP to retain ice interactivity under stressed environmental conditions was determined via (1) a modified splat assay to determine ice recrystallization inhibition (IRI) of polycrystalline ice and (2) nanoliter osmometry to evaluate the ability of MpIBP to dynamically shape the morphology of a single ice crystal. Circular dichroism (CD) was used to relate the IRI and DIS activity of MpIBP to secondary structure. The results illustrate that MpIBP secondary structure was stable between pH 6 and pH 10. It was found that MpIBP did not interact with ice at pH=4 or pH=13. At 6=pH=12 MpIBP exhibited a reduction in grain size of ice crystals as compared to control solutions and demonstrated dynamic ice shaping at 6=pH=10. The results substantiate that MpIBP retains some secondary structure and function in non-neutral pH environments; thereby, enabling its potential utility in nonphysiological materials science and engineering applications.

antifreeze proteins↗

DOE OSTI2022

A modified thermodynamic sea ice model and its application

This paper presents a modified thermodynamic sea ice model based on the Winton’s three-layer model framework. Several improvements focused on the vertical thermodynamics have been made in the model. Results from a series of one-dimensional experiments show that equilibrium ice thickness in our modified model is increased by about 45 cm when compared with the original Winton’s model. Sensitivity tests indicate that all modifications mentioned above contribute to this change of ice thickness, among which the increase of ice layer has the most significant effect followed by the sea ice conductivity parameterization. The modified thermodynamic sea ice model is then coupled into the sea ice component SIS in GFDL MOM4 to exert long-term integration experiments forced by CORE2.0 data. Results indicate that the modified model shows significant improvement in simulating the Arctic sea ice, including an increase in both the sea ice thickness and volume over the whole Arctic region. This confirms the above founding from 1-D simulations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Important ice processes are missed by the Community Earth System Model (CESM) in Southern Ocean mixed–phase clouds: Bridging SOCRATES observations to model developments

Global climate models (GCMs) are challenged by difficulties in simulating cloud phase and cloud radiative effect over the Southern Ocean (SO). Some of the new generation GCMs predict too much liquid and too little ice in mixed-phase clouds. This misrepresentation of cloud phase in GCMs results in weaker negative cloud feedback over the SO and a higher climate sensitivity. Based on a model comparison with observational data obtained during the Southern Ocean Cloud Radiation and Aerosol Transport Experimental Study (SOCRATES), this study addresses a key uncertainty in the Community Earth System Model version 2 (CESM2) related to cloud phase, namely ice formation in pristine remote SO clouds. It is found that sea spray organic aerosols (SSOA) are the most important type of ice nucleating particles (INPs) over the SO with concentrations one order of magnitude higher than those of dust INPs based on measurements and CESM2 simulations. Secondary ice production (SIP) which includes riming splintering, rain droplet shattering, and ice-ice collisional fragmentation as implemented in CESM2 is the dominant ice production process in moderately cold clouds with cloud temperatures greater than –20°C. SIP enhances the in-cloud ice number concentrations (Ni) by 1-3 orders of magnitude and predicts more mixed-phase (with percentage occurrence increased from 15% to 21%), in better agreement with the observations. Finally, this study highlights the importance of accurately representing cloud phase over the pristine remote SO by considering the ice nucleation of SSOA and SIP processes, which are currently missing in most GCM cloud microphysics parameterizations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Measurements of 14 C in ancient ice from Taylor Glacier, Antarctica constrain in situ cosmogenic 14 CH 4 and 14 CO production rates

Carbon-14 ( 14 C) is incorporated into glacial ice by trapping of atmospheric gases as well as direct near-surface in situ cosmogenic production. 14 C of trapped methane ( 14 CH 4 ) is a powerful tracer for past CH 4 emissions from “old” carbon sources such as permafrost and marine CH 4 clathrates. 14 C in trapped carbon dioxide ( 14 CO 2 ) can be used for absolute dating of ice cores. In situ produced cosmogenic 14 C in carbon monoxide ( 14 CO) can potentially be used to reconstruct the past cosmic ray flux and past solar activity. Unfortunately, the trapped atmospheric and in situ cosmogenic components of 14 C in glacial ice are difficult to disentangle and a thorough understanding of the in situ cosmogenic component is needed in order to extract useful information from ice core 14 C. Here, we analyzed very large (≈1000 kg) ice samples in the 2.26–19.53 m depth range from the ablation zone of Taylor Glacier, Antarctica, to study in situ cosmogenic production of 14 CH 4 and 14 CO. All sampled ice is >50 ka in age, allowing for the assumption that most of the measured 14 C originates from recent in situ cosmogenic production as ancient ice is brought to the surface via ablation. Our results place the first constraints on cosmogenic 14 CH 4 production rates and improve on prior estimates of 14 CO production rates in ice. We find a constant 14 CH 4 / 14 CO production ratio (0.0076 ± 0.0003) for samples deeper than 3 m, which allows the use of 14 CO for correcting the 14 CH 4 signals for the in situ cosmogenic component. Our results also provide the first unambiguous confirmation of 14 C production by fast muons in a natural setting (ice or rock) and suggest that the 14 C production rates in ice commonly used in the literature may be too high.

58 GEOSCIENCES↗

DOE OSTI2012

Importance of aerosol composition, mixing state, and morphology for heterogeneous ice nucleation: A combined field and laboratory approach

In this study chemical compositions of background aerosol and ice nuclei were examined through laboratory investigations using Raman spectroscopy and field measurements by single-particle mass spectrometry. Aerosol sampling took place at Storm Peak Laboratory in Steamboat Springs, Colorado (elevation of 3210 m). A cascade impactor was used to collect coarse-mode aerosol particles for laboratory analysis by Raman spectroscopy; the composition, mixing state, and heterogeneous ice nucleation activity of individual particles were examined. For in situ analysis of fine-mode aerosol, ice nucleation on ambient particles was observed using a compact ice nucleation chamber. Ice crystals were separated from unactivated aerosol using a pumped counterflow virtual impactor, and ice nuclei were analyzed using particle analysis by laser mass spectrometry. For both fine and coarse modes, the ice nucleating particle fractions were enriched in minerals and depleted in sulfates and nitrates, compared to the background aerosol sampled. The vast majority of particles in both the ambient and ice active aerosol fractions contained a detectable amount of organic material. Raman spectroscopy showed that organic material is sometimes present in the form of a coating on the surface of inorganic particles. We find that some organic-containing particles serve as efficient ice nuclei while others do not. For coarse-mode aerosol, organic particles were only observed to initiate ice formation when oxygen signatures were also present in their spectra.

58 GEOSCIENCES↗

DOE OSTI2018

An Overview of Interactions and Feedbacks Between Ice Sheets and the Earth System

Abstract Ice sheet response to forced changes—such as that from anthropogenic climate forcing—is closely regulated by two‐way interactions with other components of the Earth system. These interactions encompass the ice sheet response to Earth system forcing, the Earth system response to ice sheet change, and feedbacks resulting from coupled ice sheet/Earth system evolution. Motivated by the impact of Antarctic and Greenland ice sheet change on future sea level rise, here we review the state of knowledge of ice sheet/Earth system interactions and feedbacks. We also describe emerging observation and model‐based methods that can improve understanding of ice sheet/Earth system interactions and feedbacks. We particularly focus on the development of Earth system models that incorporate current understanding of Earth system processes, ice dynamics, and ice sheet/Earth system couplings. Such models will be critical tools for projecting future sea level rise from anthropogenically forced ice sheet mass loss.

Fyke, Jeremy↗

DOE OSTI2021

Improved Convective Ice Microphysics Parameterization in the NCAR CAM Model

Partitioning deep convective cloud condensates into components that sediment and detrain, known to be a challenge for global climate models, is important for cloud vertical distribution and anvil cloud formation. In this study, we address this issue by improving the convective microphysics scheme in the National Center for Atmospheric Research Community Atmosphere Model version 5.3 (CAM5.3). The improvements include: (1) considering sedimentation for cloud ice crystals that do not fall in the original scheme, (2) applying a new terminal velocity parameterization that depends on the environmental conditions for convective snow, (3) adding a new hydrometeor category, “rimed ice,” to the original four-class (cloud liquid, cloud ice, rain, and snow) scheme, and (4) allowing convective clouds to detrain snow particles into stratiform clouds. Results from the default and modified CAM5.3 models were evaluated against observations from the U.S. Department of Energy Tropical Warm Pool-International Cloud Experiment (TWP-ICE) field campaign. The default model overestimates ice amount, which is largely attributed to the underestimation of convective ice particle sedimentation. By considering cloud ice sedimentation and rimed ice particles and applying a new convective snow terminal velocity parameterization, the vertical distribution of ice amount is much improved in the midtroposphere and upper troposphere when compared to observations. The vertical distribution of ice condensate also agrees well with observational best estimates upon considering snow detrainment. Further, comparison with observed convective updrafts reveals that current bulk model fails to reproduce the observed updraft magnitude and occurrence frequency, suggesting spectral distributions be required to simulate the subgrid updraft heterogeneity.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Air‐Ice‐Ocean Coupling During a Strong Mid‐Winter Cyclone: Observing Coupled Dynamic Interactions Across Scales

Abstract Arctic cyclones are key drivers of sea ice and ocean variability. During the 2019–2020 Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, joint observations of the coupled air‐ice‐ocean system were collected at multiple spatial scales. Here, we present observations of a strong mid‐winter cyclone that impacted the MOSAiC site as it drifted in the central Arctic pack ice. The sea ice dynamical response showed spatial structure at the scale of the evolving and translating cyclonic wind field. Internal ice stress and ocean stress play significant roles, resulting in timing offsets between the atmospheric forcing and the ice response and post‐cyclone inertial ringing in the ice and ocean. Ice motion in response to the wind field then forces the upper ocean currents through frictional drag. The strongest impacts to the sea ice and ocean from the passing cyclone occur as a result of the surface impacts of a strong atmospheric low‐level jet (LLJ) behind the trailing cold front and changing wind directions between the warm‐sector LLJ and post cold‐frontal LLJ. Impacts of the cyclone are prolonged through the coupled ice‐ocean inertial response. Local impacts of the approximately 120 km wide LLJ occur over a 12 hr period or less and at scales of a kilometer to a few tens of kilometers, meaning that these impacts occur at combined smaller spatial scales and faster time scales than most satellite observations and coupled Earth system models can resolve.

Meteorology & Atmospheric Sciences↗

DOE OSTI2023

A first-principles machine-learning force field for heterogeneous ice nucleation on microcline feldspar

The formation of ice in the atmosphere affects precipitation and cloud properties, and plays a key role in the climate of our planet. Although ice can form directly from liquid water at deeply supercooled conditions, the presence of foreign particles can aid ice formation at much warmer temperatures. Over the past decade, experiments have highlighted the remarkable efficiency of feldspar minerals as ice nuclei compared to other particles present in the atmosphere. However, the exact mechanism of ice formation on feldspar surfaces has yet to be fully understood. Here, we develop a first-principles machine-learning model for the potential energy surface aimed at studying ice nucleation at microcline feldspar surfaces. The model is able to reproduce with high-fidelity the energies and forces derived from density-functional theory (DFT) based on the SCAN exchange and correlation functional. Our training set includes configurations of bulk supercooled water, hexagonal and cubic ice, microcline, and fully-hydroxylated feldspar surfaces exposed to vacuum, liquid water, and ice. In this work, we apply the machine-learning force field to study different fully-hydroxylated terminations of the (100), (010), and (001) surfaces of microcline exposed to vacuum. Our calculations suggest that terminations that do not minimize the number of broken bonds are preferred in vacuum. We also study the structure of supercooled liquid water in contact with microcline surfaces, and find that water density correlations extend up to around 10 Å from the surfaces. Finally, we show that the force field maintains a high accuracy during the simulation of ice formation at microcline surfaces, even for large systems of around 30,000 atoms. Future work will be directed towards the calculation of nucleation free energy barriers and rates using the force field developed herein, and understanding the role of different microcline surfaces on ice nucleation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗