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At least 919 records · Page 51

CICE, The Los Alamos Sea Ice Model

The Los Alamos sea ice model (CICE) is the result of an effort to develop a computationally efficient sea ice component for a fully coupled atmosphere–land–ocean–ice global climate model. It was originally designed to be compatible with the Parallel Ocean Program (POP), an ocean circulation model developed at Los Alamos National Laboratory for use on massively parallel computers. CICE has several interacting components: a vertical thermodynamic model that computes local growth rates of snow and ice due to vertical conductive, radiative and turbulent fluxes, along with snowfall; an elastic-viscous-plastic model of ice dynamics, which predicts the velocity field of the ice pack based on a model of the material strength of the ice; an incremental remapping transport model that describes horizontal advection of the areal concentration, ice and snow volume and other state variables; and a ridging parameterization that transfers ice among thickness categories based on energetic balances and rates of strain. It also includes a biogeochemical model that describes evolution of the ice ecosystem. The CICE sea ice model is used for climate research as one component of complex global earth system models that include atmosphere, land, ocean and biogeochemistry components. It is also used for operational sea ice forecasting in the polar regions and in numerical weather prediction models.

Hunke, Elizabeth↗

Real-Time Ice Nuclei Measurements at Oliktok Point Field Campaign Report

The ability of atmospheric particles (aerosols) to serve as heterogeneous ice nuclei (IN) for formation of ice and mixed-phase clouds is one of the least understood microphysical processes resulting in large uncertainties in climate modeling. As stated in the Intergovernmental Panel on Climate Change 2007 report, “The effects of aerosol particles on heterogeneous ice formation are currently insufficiently understood and present another level of challenge for both observations and modeling.” IN can strongly affect cloud radiative properties and precipitation formation. Only a small fraction (often less than 1%) of all aerosol particles act as atmospheric IN. Therefore, it becomes important to identify the active fraction of aerosol particles under a variety of environmental conditions. Proposed IN measurement techniques provide IN concentrations as a function of temperature and humidity conditions, and this unique data set can be analyzed to develop or constrain IN parameterizations that models rely on to calculate primary ice formation. Currently, the processes of ice formation within models are poorly represented, such that climate models often inaccurately partition cloud water between liquid and solid ice. Model studies have shown that uncertainties in cloud phase partitioning induce large uncertainties in the impact of mixedphase clouds on climate change. Arctic clouds composed of ice particles and supercooled liquid droplets at temperatures warmer than -37°C are important for the Arctic’s climate because of their extensive horizontal coverage over long periods, and their impact on the surface radiative balance and thus ice sheet coverage. The complexity of microphysical processes within these clouds and the sensitivity of precipitation to the details of microphysics are not fully understood. In addition, representation of these processes in a variety of cloud models continues to be challenging. Arctic clouds provide unique conditions to understand heterogeneous ice nucleation mechanisms, particularly immersion freezing, and will be the initial focus of the ice nucleation group. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM)-North Slope of Alaska (NSA) site is well equipped with other aerosol measurement (number concentration, size) instruments, and a relationship among long-term IN measurements and aerosol physical and chemical properties under different environmental conditions can be identified and established. The long-term IN measurements will be critical for understanding the ice nucleation process in response to the seasonal variations of aerosol and developing robust ice nucleation parameterizations for cloud and climate models. In the future, IN measurements could also be made at other ARM-NSA sites, specifically, Oliktok Point.

Arctic processes (meteorology), Oliktok Point, aer↗

The De-Icing Comparison Experiment – ARM Contribution (DICEXACO) Field Campaign Report

Longwave and shortwave radiative fluxes are fundamental quantities regularly observed globally using broadband radiometers. In regions conducive to frost, rime, and snow, ice frequently builds up on sensor windows, contaminating measurements. Since icing occurs under particular meteorological conditions, associated data loss constitutes a climatological bias. Furthermore, the signal caused by ice is difficult to distinguish from that of clouds, hampering efforts to identify contaminated data in post-processing. Because of the sensitivity of radiometers to internal temperature instabilities, there are limitations to using heat as a de-icing method, and consequently substantial amounts of data are lost. The De-Icing Comparison Experiment (D-ICE) was a campaign carried out at $Utqia\dot{g}vik$ (formerly known as Barrow) and Oliktok Point, Alaska, from August 2017 to July 2018. The purpose of D-ICE was to evaluate ventilation and heating technologies developed to mitigate radiometer icing. D-ICE consisted of 20 pyranometers and 5 pyrgeometers operating in various ventilator housings alongside operational stations run by the NOAA Global Monitoring Division (GMD) at NOAA’s Barrow Atmospheric Baseline Observatory. D-ICE also evaluated the sky radiometer (SKYRAD) systems at the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) and Oliktok Point (OLI; third ARM Mobile Facility [AMF3]) observatories. In total, 34 systems were evaluated (8 of which were SKYRAD radiometers). All radiometers were monitored continuously using cameras, and a total of more than one million images of sensor domes were archived collectively between the stations. Data collected as part of D-ICE by NOAA can be found through the project web page, https://www.esrl.noaa.gov/psd/arctic/d-ice/. The DICEXACO component of D-ICE (https://www.arm.gov/research/campaigns/nsa2017dicexaco) are the images collected at 10-min intervals at both OLI and NSA and are the subject of this report. Two cameras were installed at each ARM station, one directed towards the SKYRAD tracker and the other towards the SKYRAD global precision spectral pyranometer (PSP).

Oliktok Point, North Slope of Alaska, SKYRAD, pyra↗

Retrievals of Arctic Sea-Ice Volume and Its Trend Significantly Affected by Interannual Snow Variability

We estimate the uncertainty of satellite-retrieved Arctic sea-ice thickness, sea-ice volume, and their trends stemming from the lack of reliable snow-thickness observations. To illustrate, we simulate a Cryosat2-type ice-thickness retrieval in an ocean-model simulation forced by atmospheric reanalysis, pretending that only freeboard is known as model output. We then convert freeboard to sea-ice thickness using different snow climatologies and compare the resulting sea-ice thickness retrievals to each other and to the real sea-ice thickness of the reanalysis-forced simulation. We postulate that different snow climatologies cause significant differences in the obtained ice thickness and ice volume. Moreover, we show that Arctic ice-volume trends derived from ice-thickness retrievals using any snow-depth climatology are highly unreliable because the estimated trend in ice volume can strongly be influenced by the neglected interannual variability in snow volume.

54 ENVIRONMENTAL SCIENCES↗

On large outflows of Arctic sea ice into the Barents Sea

Winter outflows of Arctic sea ice into the Barents Sea are estimated using a 10-year record of satellite ice motion and thickness. The mean winter volume export through the Svalbard/Franz Josef Land passage is 40 km3, and ranges from -280 km3 to 340 km3. A large outflow in 2003 is preconditioned by an unusually high concentration of thick perennial ice over the Nansen Basin at the end of the 2002 summer. With a deep atmospheric low situated over the eastern Barents Sea in winter, the result is an increased export of Arctic ice. The Oct-Mar ice area flux, at 110 x 10 to the third power km3, is not only unusual in magnitude but also remarkable in that >70% of the area is multiyear ice; the ice volume flux at~340 km3 is almost one-fifth of the ice flux through the Fram Strait. Another large outflow of Arctic sea ice through this passage, comparable to that in 2003, is found in 1996. This southward flux of sea ice represents one of two major sources of freshwater in the Barents Sea; the other is the eastward flux of water via the Norwegian Coastal Current. The possible consequences of variable freshwater input on the Barents Sea hydrography and its impact on transformation of Atlantic Water en route to the Arctic Ocean are examined with a 25-year coupled ice-ocean model.

Artic ice↗

Annual Cycles of Multiyear Sea Ice Coverage of the Arctic Ocean: 1999-2003

For the years 1999-2003, we estimate the time-varying perennial ice zone (PIZ) coverage and construct the annual cycles of multiyear (MY, including second year) ice coverage of the Arctic Ocean using QuikSCAT backscatter, MY fractions from RADARSAT, and the record of ice export from satellite passive microwave observations. An area balance approach extends the winter MY coverage from QuikSCAT to the remainder of the year. From these estimates, the coverage of MY ice at the beginning of each year is 3774 x 10(exp 3) sq km (2000), 3896 x 10(exp 3) sq km (2001), 4475 x 10(exp 3) sq km (2002), and 4122 x 10(exp 3) sq km (2003). Uncertainties in coverage are approx.150 x 10(exp 3) sq km. In the mean, on 1 January, MY ice covers approx.60% of the Arctic Ocean. Ice export reduces this coverage to approx.55% by 1 May. From the multiple annual cycles, the area of first-year (FY) ice that survives the intervening summers are 1192 x 10(exp 3) sq km (2000), 1509 x 10(exp 3) sq km (2001), and 582 x 10(exp 3) sq km (2002). In order for the MY coverage to remain constant from year to year, these replenishment areas must balance the overall area export and melt during the summer. The effect of the record minimum in Arctic sea ice area during the summer of 2002 is seen in the lowest area of surviving FY ice of the three summers. In addition to the spatial coverage, the location of the PIZ is important. One consequence of the unusual location of the PIZ at the end of the summer of 2002 is the preconditioning for enhanced export of MY ice into the Barents and Kara seas. Differences between the minimums in summer sea ice coverage from our estimates and passive microwave observations are discussed.

Arctic Ocean↗

Test Results for the SEA Ice Crystal Detector (ICD) under SLD Conditions at the NASA IRT

The Science Engineering Associates hot-wire Ice Crystal Detector was tested under Appendix C and Supercooled Large Drop Conditions at the NASA Icing Research Tunnel, with the purpose of comparing the measurements to the tunnel LWC calibration, and to test the performance of the mixed-phase retrievals of the probe. The liquid water content measured by the total water content sensor of the probe agreed well with the tunnel calibration over a wide range of MVDs, not unexpectedly since the tunnel was calibrated with a similar Multiwire hot-wire probe. A scale factor difference of about 7% was attributed to the lack of an efficiency correction for the Ice Crystal Detector at smaller median volume diameters, and typical sample area uncertainties of liquid water content devices. In addition, the simultaneous equations that are used to retrieve liquid and ice water contents were tested under liquid and glaciated conditions. Using constant ice and water efficiencies for each wire, the equations were found to produce a large and false ice water content retrieval in large median volume diameter liquid cases. By applying a liquid efficiency to the liquid water content sensor that varied with median volume diameter, retrievals were improved such that false ice water content was less than ±10% of the total water content out to the 460 μm median volume diameter limit of the testing. The probe was also tested in glaciated conditions by freezing out a small median volume diameter spray. Using constant ice efficiencies for the two sensors provided from aircraft measurements, the retrieved ice water content was about 40% higher than expected for the case presented, likely due to the ice efficiencies that were used from aircraft measurements of natural clouds being too low for the tunnel’s glaciated sprays. Application of ice efficiencies that vary with particle size and potentially other parameters will be explored for future improvement of retrievals.

Air Craft Icing↗

Test Results for the SEA Ice Crystal Detector (ICD) under SLD Conditions at the NASA IRT

The Science Engineering Associates hot-wire Ice Crystal Detector was tested under Appendix C and Supercooled Large Drop Conditions at the NASA Icing Research Tunnel, with the purpose of comparing the measurements to the tunnel LWC calibration, and to test the performance of the mixed-phase retrievals of the probe. The liquid water content measured by the total water content sensor of the probe agreed well with the tunnel calibration over a wide range of MVDs, not unexpectedly since the tunnel was calibrated with a similar Multiwire hot-wire probe. A scale factor difference of about 7% was attributed to the lack of an efficiency correction for the Ice Crystal Detector at smaller median volume diameters, and typical sample area uncertainties of liquid water content devices. In addition, the simultaneous equations that are used to retrieve liquid and ice water contents were tested under liquid and glaciated conditions. Using constant ice and water efficiencies for each wire, the equations were found to produce a large and false ice water content retrieval in large median volume diameter liquid cases. By applying a liquid efficiency to the liquid water content sensor that varied with median volume diameter, retrievals were improved such that false ice water content was less than ±10% of the total water content out to the 460 μm median volume diameter limit of the testing. The probe was also tested in glaciated conditions by freezing out a small median volume diameter spray. Using constant ice efficiencies for the two sensors provided from aircraft measurements, the retrieved ice water content was about 40% higher than expected for the case presented, likely due to the ice efficiencies that were used from aircraft measurements of natural clouds being too low for the tunnel’s glaciated sprays. Application of ice efficiencies that vary with particle size and potentially other parameters will be explored for future improvement of retrievals.

o Aircraft Icing↗

Long-lifetime ice particles in mixed-phase stratiform clouds: Quasi-steady and recycled growth

Lagrangian ice particle tracking is applied in both a 3-D time dependent velocity field produced by a Large Eddy Simulation cloud model and in a 2-D idealized field. It is found that more than 10% of ice particles have lifetimes longer than 1.5 hours, much longer than the large eddy turnover time or the time for a crystal to fall through the depth of a non-turbulent cloud. An analysis of trajectories in a 2-D idealized field shows that there are two types of long lifetime ice particles: quasi-steady and recycled growth. For quasi-steady growth, ice particles are suspended in the updraft velocity region for a long time. For recycled growth, ice particles are trapped in the large-eddy structures, and whether ice particles grow or evaporate depends on the ice relative humidity profile within the boundary layer. Some ice particles can grow after each cycle in the trapping region, until they are too large to be trapped, and thus have long lifetimes. Here, the relative contribution of the recycled ice particles to the cloud mean ice water content depends on both the dynamic and thermodynamic properties of the mixing layer. In particular, the total ice water content of a mixed phase cloud in a decoupled boundary layer can be much larger than that in a fully coupled boundary layer.

54 ENVIRONMENTAL SCIENCES↗

The Role of Organic Aerosol in Atmospheric Ice Nucleation: A Review

Predicting the formation of ice crystals in the atmosphere presents one of the great challenges in physical sciences with important implications for the chemistry and composition of the Earth’s atmosphere, the hydrological cycle, and climate. Among atmospheric ice formation processes, heterogeneous ice nucleation proceeds on aerosol particles ranging from a few nanometers to micrometers in size, commonly referred to as ice nucleating particles (INPs). Research over the last two decades has demonstrated that organic matter (OM) is ubiquitous in the atmosphere, present as organic aerosol (OA) particles or as coatings on other particle types. While it is well understood that mineral dust particles can induce ice nucleation under atmospheric conditions, it is currently not clear how much OA particles including pollution aerosol and secondary organic aerosol (SOA) contributes to the ambient INP population. The physicochemical properties of OM make predicting how OM interacts with water vapor leading ultimately to ice crystals challenging. This review focuses on the role of OM in INPs, summarizing and highlighting recent advances in our understanding of the ice nucleation process gained from theoretical, laboratory, and field studies. Examination of ice residuals and INPs with analytical techniques demonstrates that OM participates in atmospheric ice crystal formation. Molecular dynamic simulations provide insight into the microscopic processes that initiate ice nucleation. The amorphous phase state of OM in the supercooled and metastable regime is identified as a key factor in assessing the particles’ nucleation pathways and rates. A theoretical model is advanced, based on particle water activity, to holistically predict amorphous phase changes and ice nucleation rates of particles coated by OM. The goal of this review is to synthesize our current understanding and propose future research directions needed to fully evaluate how OA particles contribute to INPs in the atmosphere.

54 ENVIRONMENTAL SCIENCES↗

Climate Impacts of Ice Nucleation

[1] Several different ice nucleation parameterizations in two different General Circulation Models (GCMs) are used to understand the effects of ice nucleation on the mean climate state, and the Aerosol Indirect Effects (AIE) of cirrus clouds on climate. Simulations have a range of ice microphysical states that are consistent with the spread of observations, but many simulations have higher present-day ice crystal number concentrations than in-situ observations. These different states result from different parameterizations of ice cloud nucleation processes, and feature different balances of homogeneous and heterogeneous nucleation. Black carbon aerosols have a small (-0.06 Wm -2 ) and not statistically significant AIE when included as ice nuclei, for nucleation efficiencies within the range of laboratory measurements. Indirect effects of anthropogenic aerosols on cirrus clouds occur as a consequence of increasing anthropogenic sulfur emissions with different mechanisms important in different models. In one model this is due to increases in homogeneous nucleation fraction, and in the other due to increases in heterogeneous nucleation with coated dust. The magnitude of the effect is the same however. The resulting ice AIE does not seem strongly dependent on the balance between homogeneous and heterogeneous ice nucleation. Regional effects can reach several Wm -2 . Indirect effects are slightly larger for those states with less homogeneous nucleation and lower ice number concentration in the base state. The total ice AIE is estimated at 0.27 ± 0.10 Wm -2 (1σ uncertainty). Finally, this represents a 20% offset of the simulated total shortwave AIE for ice and liquid clouds of -1.6 Wm -2 .

climate↗

Cloud Properties and Boundary Layer Stability Above Southern Ocean Sea Ice and Coastal Antarctica

Significant variability in climate predictions originates from the simulated cloud cover over the Southern Ocean. Historically, Southern Ocean cloud and aerosol properties have been less studied than their northern hemisphere counterparts, and cloud-sea-ice interactions over the Southern Ocean also remain largely unexamined. We used data from combined radar, lidar, radiometer, radiosonde, and ERA5 reanalysis profiles to investigate cloud property relationships to cloud temperature, sea-ice concentration, and boundary layer stability. Our findings show correlations between both cloud macrophysical properties and radiative effects and sea-ice concentration, and that the marine atmospheric boundary layer is more stable over higher sea-ice concentrations. Mixed-phase cloud frequency of occurrence was highest over the sea-ice zone at 15%, three times higher than over cold water south of the Antarctic Polar Front. For temperatures greater than –15°C, low-level, single-layer clouds were more likely to precipitate ice if they were coupled to cold-water or sea-ice surfaces than if they were decoupled from these surfaces, with the highest percentage of clouds precipitating ice observed over sea ice. These findings suggest a surface source of ice-nucleating particles at high southern latitudes that increases cloud glaciation probability. We discuss the implications of our results for future studies into the relationship between cloud properties, aerosols, sea ice, and boundary layer stability at high latitudes over the Southern Ocean.

54 ENVIRONMENTAL SCIENCES↗

Seismic Tremors From Sea‐Landfast Ice Interactions Near Utqiaġvik, Alaska

The mechanical state of Arctic landfast sea ice remains poorly constrained due to limited observations. This study investigates interactions between drifting sea ice and the coastal landfast ice near Utqiaġvik, Alaska by integrating data from broadband seismometer, Distributed Acoustic Sensing, and marine radar. We find that decreases in sea ice velocity, marking transitions from drift to compressive contact, coincide with increased seismic energy. Tremor characteristics vary seasonally with ice conditions. In January, dense ice packs produced sustained harmonic tremors with gliding and U-shaped spectral features, consistent with repetitive stick-slip motion at the ice–ice or ice–ground interface under velocity-weakening friction. In April, smaller fragmented floes generated short-lived, chaotic tremors linked to brittle failure and spatially dispersed impacts. These findings demonstrate that seismic tremors encode the mechanical properties of interacting ice, offering a new tool to distinguish ice regimes and monitor evolving Arctic coastal dynamics under climate change.

58 GEOSCIENCES↗

CO DIFFUSION INTO AMORPHOUS H{sub 2}O ICES

The mobility of atoms, molecules, and radicals in icy grain mantles regulates ice restructuring, desorption, and chemistry in astrophysical environments. Interstellar ices are dominated by H{sub 2}O, and diffusion on external and internal (pore) surfaces of H{sub 2}O-rich ices is therefore a key process to constrain. This study aims to quantify the diffusion kinetics and barrier of the abundant ice constituent CO into H{sub 2}O-dominated ices at low temperatures (15–23 K), by measuring the mixing rate of initially layered H{sub 2}O(:CO{sub 2})/CO ices. The mixed fraction of CO as a function of time is determined by monitoring the shape of the infrared CO stretching band. Mixing is observed at all investigated temperatures on minute timescales and can be ascribed to CO diffusion in H{sub 2}O ice pores. The diffusion coefficient and final mixed fraction depend on ice temperature, porosity, thickness, and composition. The experiments are analyzed by applying Fick’s diffusion equation under the assumption that mixing is due to CO diffusion into an immobile H{sub 2}O ice. The extracted energy barrier for CO diffusion into amorphous H{sub 2}O ice is ∼160 K. This is effectively a surface diffusion barrier. The derived barrier is low compared to current surface diffusion barriers in use in astrochemical models. Its adoption may significantly change the expected timescales for different ice processes in interstellar environments.

74 ATOMIC AND MOLECULAR PHYSICS↗

Implementation and Initial Evaluation of the Glimmer Community Ice Sheet Model in the Community Earth System Model

The Glimmer Community Ice Sheet Model (Glimmer-CISM) has been implemented in the Community Earth System Model (CESM). Glimmer-CISM is forced by a surface mass balance (SMB) computed in multiple elevation classes in the CESM land model and downscaled to the ice sheet grid. Ice sheet evolution is governed by the shallow-ice approximation with thermomechanical coupling and basal sliding. This paper describes and evaluates the initial model implementation for the Greenland Ice Sheet (GIS). The ice sheet model was spun up using the SMB from a coupled CESM simulation with preindustrial forcing. The model's sensitivity to three key ice sheet parameters was explored by running an ensemble of 100 GIS simulations to quasi equilibrium and ranking each simulation based on multiple diagnostics. With reasonable parameter choices, the steady-state GIS geometry is broadly consistent with observations. The simulated ice sheet is too thick and extensive, however, in some marginal regions where the SMB is anomalously positive. The top-ranking simulations were continued using surface forcing from CESM simulations of the twentieth century (1850–2005) and twenty-first century (2005–2100, with RCP8.5 forcing). In these simulations the GIS loses mass, with a resulting global-mean sea level rise of 16 mm during 1850–2005 and 60 mm during 2005–2100. This mass loss is caused mainly by increased ablation near the ice sheet margin, offset by reduced ice discharge to the ocean. Projected sea level rise is sensitive to the initial geometry, showing the importance of realistic geometry in the spun-up ice sheet.

54 ENVIRONMENTAL SCIENCES↗

Arctic Sea Ice Volume Variability over 1901–2010: A Model-Based Reconstruction

PIOMAS-20C, an Arctic sea ice reconstruction for 1901–2010, is produced by forcing the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) with ERA-20C atmospheric data. ERA-20C performance over Arctic sea ice is assessed by comparisons with measurements and data from other reanalyses. ERA-20C performs similarly with respect to the annual cycle of downwelling radiation, air temperature, and wind speed compared to reanalyses with more extensive data assimilation such as ERA-Interim and MERRA. PIOMAS-20C sea ice thickness and volume are then compared with in situ and aircraft remote sensing observations for the period of ~1950–2010. Error statistics are similar to those for PIOMAS. We compare the magnitude and patterns of sea ice variability between the first half of the twentieth century (1901–40) and the more recent period (1980–2010), both marked by sea ice decline in the Arctic. The first period contains the so-called early-twentieth-century warming (ETCW; ~1920–40) during which the Atlantic sector saw a significant decline in sea ice volume, but the Pacific sector did not. The sea ice decline over the 1979–2010 period is pan-Arctic and 6 times larger than the net decline during the 1901–40 period. Sea ice volume trends reconstructed solely from surface temperature anomalies are smaller than PIOMAS-20C, suggesting that mechanisms other than warming, such as changes in ice motion and deformation, played a significant role in determining sea ice volume trends during both periods.

54 ENVIRONMENTAL SCIENCES↗

Final Technical Report for "Ice nuclei relation to aerosol properties: Data analysis and model parameterization for IN in mixed-phase clouds" (DOE/SC00002354)

Clouds play an important role in weather and climate. In addition to their key role in the hydrologic cycle, clouds scatter incoming solar radiation and trap infrared radiation from the surface and lower atmosphere. Despite their importance, feedbacks involving clouds remain as one of the largest sources of uncertainty in climate models. To better simulate cloud processes requires better characterization of cloud microphysical processes, which can affect the spatial extent, optical depth and lifetime of clouds. To this end, we developed a new parameterization to be used in numerical models that describes the variation of ice nuclei (IN) number concentrations active to form ice crystals in mixed-phase (water droplets and ice crystals co-existing) cloud conditions as these depend on existing aerosol properties and temperature. The parameterization is based on data collected using the Colorado State University continuous flow diffusion chamber in aircraft and ground-based campaigns over a 14-year period, including data from the DOE-supported Mixed-Phase Arctic Cloud Experiment. The resulting relationship is shown to more accurately represent the variability of ice nuclei distributions in the atmosphere compared to currently used parameterizations based on temperature alone. When implemented in one global climate model, the new parameterization predicted more realistic annually averaged cloud water and ice distributions, and cloud radiative properties, especially for sensitive higher latitude mixed-phase cloud regions. As a test of the new global IN scheme, it was compared to independent data collected during the 2008 DOE-sponsored Indirect and Semi-Direct Aerosol Campaign (ISDAC). Good agreement with this new data set suggests the broad applicability of the new scheme for describing general (non-chemically specific) aerosol influences on IN number concentrations feeding mixed-phase Arctic stratus clouds. Finally, the parameterization was implemented into a regional cloud-resolving model to compare predictions of ice crystal concentrations and other cloud properties to those observed in two intensive case studies of Arctic stratus during ISDAC. Our implementation included development of a prognostic scheme of ice activation using the IN parameterization so that the most realistic treatment of ice nuclei, including their budget (gains and losses), was achieved. Many cloud microphysical properties and cloud persistence were faithfully reproduced, despite a tendency to under-predict (by a few to several times) ice crystal number concentrations and cloud ice mass, in agreement with some other studies. This work serves generally as the basis for improving predictive schemes for cloud ice crystal activation in cloud and climate models, and more specifically as the basis for such a scheme to be used in a Multi-scale Modeling Format (MMF) that utilizes a connected system of cloud-resolving models on a global grid in an effort to better resolve cloud processes and their influence on climate.

54 ENVIRONMENTAL SCIENCES↗

Modeling the Fracture of Ice Sheets on Parallel Computers

The objective of this project was to investigate the complex fracture of ice and understand its role within larger ice sheet simulations and global climate change. This objective was achieved by developing novel physics based models for ice, novel numerical tools to enable the modeling of the physics and by collaboration with the ice community experts. At the present time, ice fracture is not explicitly considered within ice sheet models due in part to large computational costs associated with the accurate modeling of this complex phenomena. However, fracture not only plays an extremely important role in regional behavior but also influences ice dynamics over much larger zones in ways that are currently not well understood. To this end, our research findings through this project offers significant advancement to the field and closes a large gap of knowledge in understanding and modeling the fracture of ice sheets in the polar regions. Thus, we believe that our objective has been achieved and our research accomplishments are significant. This is corroborated through a set of published papers, posters and presentations at technical conferences in the field. In particular significant progress has been made in the mechanics of ice, fracture of ice sheets and ice shelves in polar regions and sophisticated numerical methods that enable the solution of the physics in an efficient way.

97 MATHEMATICS AND COMPUTING↗