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At least 199 records · Page 11

Importance of aggregation and small ice crystals in cirrus clouds, based on observations and an ice particle growth model

The 1 November 1986 FIRE I case study was used to test an ice particle growth model which predicts bimodal size spectra in cirrus clouds. The model was developed from an analytically based model which predicts the height evolution of monomodal ice particle size spectra from the measured ice water content (IWC). Size spectra from the monomodal model are represented by a gamma distribution, N(D) = N(sub o)D(exp nu)exp(-lambda D), where D = ice particle maximum dimension. The slope parameter, lambda, and the parameter N(sub o) are predicted from the IWC through the growth processes of vapor diffusion and aggregation. The model formulation is analytical, computationally efficient, and well suited for incorporation into larger models. The monomodal model has been validated against two other cirrus cloud case studies. From the monomodal size spectra, the size distributions which determine concentrations of ice particles less than about 150 mu m are predicted.

Mitchell, David L.↗

Free oscillations in a climate model with ice-sheet dynamics

A study of stable periodic solutions to a simple nonlinear model of the ocean-atmosphere-ice system is presented. The model has two dependent variables: ocean-atmosphere temperature and latitudinal extent of the ice cover. No explicit dependence on latitude is considered in the model. Hence all variables depend only on time and the model consists of a coupled set of nonlinear ordinary differential equations. The globally averaged ocean-atmosphere temperature in the model is governed by the radiation balance. The reflectivity to incoming solar radiation, i.e., the planetary albedo, includes separate contributions from sea ice and from continental ice sheets. The major physical mechanisms active in the model are (1) albedo-temperature feedback, (2) continental ice-sheet dynamics and (3) precipitation-rate variations. The model has three-equilibrium solutions, two of which are linearly unstable, while one is linearly stable. For some choices of parameters, the stability picture changes and sustained, finite-amplitude oscillations obtain around the previously stable equilibrium solution. The physical interpretation of these oscillations points to the possibility of internal mechanisms playing a role in glaciation cycles.

Kallen, E.↗

ISSM: Ice Sheet System Model

In order to have the capability to use satellite data from its own missions to inform future sea-level rise projections, JPL needed a full-fledged ice-sheet/iceshelf flow model, capable of modeling the mass balance of Antarctica and Greenland into the near future. ISSM was developed with such a goal in mind, as a massively parallelized, multi-purpose finite-element framework dedicated to ice-sheet modeling. ISSM features unstructured meshes (Tria in 2D, and Penta in 3D) along with corresponding finite elements for both types of meshes. Each finite element can carry out diagnostic, prognostic, transient, thermal 3D, surface, and bed slope simulations. Anisotropic meshing enables adaptation of meshes to a certain metric, and the 2D Shelfy-Stream, 3D Blatter/Pattyn, and 3D Full-Stokes formulations capture the bulk of the ice-flow physics. These elements can be coupled together, based on the Arlequin method, so that on a large scale model such as Antarctica, each type of finite element is used in the most efficient manner. For each finite element referenced above, ISSM implements an adjoint. This adjoint can be used to carry out model inversions of unknown model parameters, typically ice rheology and basal drag at the ice/bedrock interface, using a metric such as the observed InSAR surface velocity. This data assimilation capability is crucial to allow spinning up of ice flow models using available satellite data. ISSM relies on the PETSc library for its vectors, matrices, and solvers. This allows ISSM to run efficiently on any parallel platform, whether shared or distrib- ISSM: Ice Sheet System Model NASA's Jet Propulsion Laboratory, Pasadena, California uted. It can run on the largest clusters, and is fully scalable. This allows ISSM to tackle models the size of continents. ISSM is embedded into MATLAB and Python, both open scientific platforms. This improves its outreach within the science community. It is entirely written in C/C++, which gives it flexibility in its design, and the power/speed that C/C++ allows. ISSM is svn (subversion) hosted, on a JPL repository, to facilitate its development and maintenance. ISSM can also model propagation of rifts using contact mechanics and mesh splitting, and can interface to the Dakota software. To carry out sensitivity analysis, mesh partitioning algorithms are available, based on the Scotch, Chaco, and Metis partitioners that ensure equal area mesh partitions can be done, which are then usable for sampling and local reliability methods.

Larour, Eric↗

Comparison of Bimodal Ice Shapes on Full-Chord and Hybrid CRM Midspan Models

An ice shape database has been created to document ice accretions on a full-chord length and hybrid versions of a 65 percent scale size of the mid-span section of the Common Research Model resulting from an exposure to a Super-cooled 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 ice accretion. 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 monomodal distributions of identical cloud droplet Median Volume Diameter (MVD) were obtained and compared. Results indicated that the ice shapes resulting from the monomodal and bimodal drop size distributions have similar 2D Maximum Combined Cross Section, or MCCS, ice shape around the model leading edge region and equivalent ice mass measurement per unit span to within the IRT SLD cloud calibration uncertainty, as expected with this approach, but the bimodal distributions have distinctly larger ice feathers that extended further back on the chord of the model. For most test conditions, the overall size and shape of the main ice accretions compared well between the full-chord and hybrid models

Icing , Simulation, Validation↗

Comparison of Bimodal Ice Shapes on Full-Chord and Hybrid CRM Midspan Models

An ice shape database has been created to document ice accretions on a full-chord length and hybrid versions of a 65 percent scale size of the mid-span section of the Common Research Model resulting from an exposure to a Super-cooled 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 ice accretion. 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 monomodal distributions of identical cloud droplet Median Volume Diameter (MVD) were obtained and compared. Results indicated that the ice shapes resulting from the monomodal and bimodal drop size distributions have similar 2D Maximum Combined Cross Section, or MCCS, ice shape around the model leading edge region and equivalent ice mass measurement per unit span to within the IRT SLD cloud calibration uncertainty, as expected with this approach, but the bimodal distributions have distinctly larger ice feathers that extended further back on the chord of the model. For most test conditions, the overall size and shape of the main ice accretions compared well between the full-chord and hybrid models.

Icing↗

Utilization of Airborne Observations to Assess Model Parametrizations of Critical RH Profiles in the Arctic Ocean

Observational paucity is a reality in the Arctic Ocean. This is especially true for near-surface variables such as temperature, moisture, heat fluxes and BL clouds. As a result, modeling has become one of the major avenues for understanding current and future Arctic trends. Reanalyses are frequently used to force global ocean circulation and sea-ice models. But in northern high latitudes, model integrations and reanalyses are known to have large uncertainties in temperature and humidity profiles, and in boundary layer cloudiness. These are common sources of error in the surface radiative budget terms.An important way to diagnose these biases spatially and temporally is by using satellite remote sensing data. However, remotely-sensed observations also have large uncertainties, especially in near-surface temperature and relative humidity profiles.In situ observational studies are important in bridging our knowledge gap in regions such as the Arctic Ocean. Here, we utilize airborne and ship observations from the ARISE, ACME-IV, and ASCOS campaigns to construct critical relative humidity (RH) profiles over the Beaufort Sea. Such profiles are used as parameterization inputs in the NASA GOES global model to derive the total water condensate in a model grid-box, which determines the cloud fraction. Currently, the critical RH profiles are derived by global AIRS data, relaying mostly on mid-latitude regions, which are not necessarily relevant to the Arctic.We derive campaign-wide mean, standard deviation, and critical RH values, for grid size of 50x50 km and altitude bins between 50 to 400 m, covering both open-ocean and sea-ice covered regions. We compare profiles over open ocean and sea-ice, and look at correlations between the observed critical RH values and water condensate (by cloud number concentration) from observations versus the modeled ones. We then input our calculated values of minimal critical RH values into a set of GEOS single column model (SCM) simulations over the ARISE and ASCOS regions and compare the differences between the predicted values of cloud liquid water path (LWP), ice water path (IWP) and surface fluxes with the observed ones under the range of input parameterizations. Finally, we discuss the implications on surface radiative budget predictions in this region.

Segal-Rozenhaimer, Michal↗

Comparison of Bimodal Ice Shapes on Full-Chord and Hybrid CRM Midspan Models

An ice shape database has been created to document ice accretions on a full-chord length and hybrid versions of a 65 percent scale size of the mid-span section of the Common Research Model resulting from an exposure to a Super-cooled 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 ice accretion. 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 monomodal distributions of identical cloud droplet Median Volume Diameter (MVD) were obtained and compared. Results indicated that the ice shapes resulting from the monomodal and bimodal drop size distributions have similar 2D Maximum Combined Cross Section, or MCCS, ice shape around the model leading edge region and equivalent ice mass measurement per unit span to within the IRT SLD cloud calibration uncertainty, as expected with this approach, but the bimodal distributions have distinctly larger ice feathers that extended further back on the chord of the model. For most test conditions, the overall size and shape of the main ice accretions compared well between the full-chord and hybrid models.

Icing↗

Physics of the Seasonal Sea Ice Zone

The seasonal sea ice zone encompasses the region between the winter maximum and summer minimum sea ice extent. In both the Arctic and Antarctic, the majority of the ice cover can now be classified as seasonal. Here, we review the sea ice physics that governs the evolution of seasonal sea ice in the Arctic and Antarctic, spanning sea ice growth, melt, and dynamics and including interactions with ocean surface waves as well as other coupled processes. The advent of coupled wave–ice modeling and discrete-element modeling, together with improved and expanded satellite observations and field campaigns, has yielded advances in process understanding. Many topics remain in need of further investigation, including rheologies appropriate for seasonal sea ice, wave-induced sea ice fracture, welding for sea ice freeze-up, and the distribution of snow on seasonal sea ice. Future research should aim to redress biases (such as disparities in focus between the Arctic and Antarctic and between summer and winter processes) and connect observations to modeling across spatial scales.

sea ice↗

Measurements of local convective heat transfer coefficients on ice accretion shapes

The thin-skin heat rate technique was used to determine local convective heat transfer coefficients for four representative ice accretion shapes. The shapes represented three stages of glaze ice formation and one rime ice formation; the ice models had varying degrees of surface roughness. In general, convective heat transfer was higher in regions where the model's surfaces were convex and lower in regions where the surfaces were concave. The effect of roughness was different for the glaze and rime ice shapes. On the glaze ice shapes, roughness increased the maximum Nu by 80 percent, but the other Nu values were virtually unchanged. On the rime ice shape, the Nu numbers near the stagnation point were unchanged. The maximum Nu value increased by 45 percent, and the Nu number downstream of the peak increased by approximately 150 percent.

Arimilli, R. V.↗

Arctic Ocean Freshwater: How Robust are Model Simulations

The Arctic freshwater (FW) has been the focus of many modeling studies, due to the potential impact of Arctic FW on the deep water formation in the North Atlantic. A comparison of the hindcasts from ten ocean-sea ice models shows that the simulation of the Arctic FW budget is quite different in the investigated models. While they agree on the general sink and source terms of the Arctic FW budget, the long-term means as well as the variability of the FW export vary among models. The best model-to-model agreement is found for the interannual and seasonal variability of the solid FW export and the solid FW storage, which also agree well with observations. For the interannual and seasonal variability of the liquid FW export, the agreement among models is better for the Canadian Arctic Archipelago (CAA) than for Fram Strait. The reason for this is that models are more consistent in simulating volume flux anomalies than salinity anomalies and volume-flux anomalies dominate the liquid FW export variability in the CAA but not in Fram Strait. The seasonal cycle of the liquid FW export generally shows a better agreement among models than the interannual variability, and compared to observations the models capture the seasonality of the liquid FW export rather well. In order to improve future simulations of the Arctic FW budget, the simulation of the salinity field needs to be improved, so that model results on the variability of the liquid FW export and storage become more robust.

Jahn, A.↗

The role of sea ice in 2 x CO2 climate model sensitivity. Part 1: The total influence of sea ice thickness and extent

As a first step in investigating the effects of sea ice changes on the climate sensitivity to doubled atmospheric CO2, the authors use a standard simple sea ice model while varying the sea ice distributions and thicknesses in the control run. Thinner ice amplifies the atmospheric temperature senstivity in these experiments by about 15% (to a warming of 4.8 C), because it is easier for the thinner ice to be removed as the climate warms. Thus, its impact on sensitivity is similar to that of greater sea ice extent in the control run, which provides more opportunity for sea ice reduction. An experiment with sea ice not allowed to change between the control and doubled CO2 simulations illustrates that the total effect of sea ice on surface air temperature changes, including cloud cover and water vapor feedbacks that arise in response to sea ice variations, amounts to 37% of the temperature sensitivity to the CO2 doubling, accounting for 1.56 C of the 4.17 C global warming. This is about four times larger than the sea ice impact when no feedbacks are allowed. The different experiments produce a range of results for southern high latitudes with the hydrologic budget over Antarctica implying sea level increases of varying magnitude or no change. These results highlight the importance of properly constraining the sea ice response to climate perturbations, necessitating the use of more realistic sea ice and ocean models.

Rind, D.↗

Winter Arctic Sea Ice Thickness from ICESat-2 Freeboards

NASA’s ICESat-2 mission was launched in September 2018 with the primary goal of monitoring our rapidly changing polar regions. The sole instrument onboard, the Advanced Topographic Laser Altimeter System (ATLAS), is now providing routine, very high-resolution, surface elevation data across the globe, including the Arctic and Southern Oceans. In this study we demonstrate our new processing chain for converting the along-track ICESat-2 sea ice freeboard product (ATL10) into sea ice thickness, focusing our initial efforts on the Arctic Ocean. For this conversion we primarily make use of snow depth and density data from the NASA Eulerian Snow on Sea Ice Model (NESOSIM). The coarse resolution (~100 km) snow data are redistributed onto the high resolution (~30 - 100 m) ATL10 freeboards using relationships obtained from snow depth and freeboard data collected by NASA’s Operation IceBridge mission. We present regional sea ice thickness distributions and highlight their seasonal evolution through our first winter-season of data collection. We include ice thickness uncertainty estimates, while also acknowledging the limitations of these estimates. We generate a gridded monthly thickness product and compare this with various monthly sea ice thickness estimates obtained from ESA’s CryoSat-2 satellite mission, with ICE 33 Sat-2 showing consistently lower thicknesses. Finally, we compare our February/March 2019 thickness estimates to ICESat February/March (19th February – 21st March) 2008 ice thickness estimates using the same input assumptions, which show a ~0.40 m or ~21% thinning across an inner Arctic Ocean domain in this 11-year time period.

Alek A Petty↗

Estimating Glaciation Temperature of Deep Convective Clouds with Remote Sensing Data

Major uncertainties exist for observing and modeling ice content inside deep convective clouds (DCC). One of the difficulties has been the lack of characterization of vertical profiles of cloud hydrometeor phase. Here we propose a technique to estimate the DCC glaciation temperature using passive remote sensing data. It is based on a conceptual model of vertical hydrometeor size profiles inside DCCs. Estimates from the technique agree well with our general understanding of the problem. Furthermore, the link between vertical profiles of cloud particle size and hydrometeor thermodynamic phase is confirmed by a 3-13 cloud retrieval technique. The technique is applied to aircraft measurements of cloud side reflectance and the result was compared favorably with an independent retrieval of thermodynamic phase based on different refractive indices at 2.13 micron and 2.25 micron. Possible applications of the technique are discussed.

Yuan, Tianle↗

Earth Observing System (EOS) Snow and Ice Products for Observation and Modeling

Snow and ice are the key components of the Earth's cryosphere, and their influence on the Earth's energy balance is very significant due at least in part to the large areal extent and high albedo characterizing these features. Large changes in the cryosphere have been measured over the last century and especially over the past decade, and remote sensing plays a pivotal role in documenting these changes. Many of NASA's Earth Observing System (EOS) products derived from instruments on the Terra, Aqua, and Ice, Cloud and land Elevation Satellite (ICESat) satellites are useful for measuring changes in features that are associated with climate change. The utility of the products is continually enhanced as the length of the time series increases. To gain a more coherent view of the cryosphere and its historical and recent changes, the EOS products may be employed together, in conjunction with other sources of data, and in models. To further this goal, the first EOS Snow and Ice Products Workshop was convened. The specific goals of the workshop were to provide current and prospective users of EOS snow and ice products up-to-date information on the products, their validation status and future enhancements, to help users utilize the data products through hands-on demonstrations, and to facilitate the integration of EOS products into models. Oral and poster sessions representing a wide variety of snow and ice topics were held; three panels were also convened to discuss workshop themes. Panel discussions focused on data fusion and assimilation of the products into models. Approximately 110 people attended, representing a wide array of interests and organizations in the cryospheric community.

Hall, D.↗

High-Resolution Modeling of the Gulf of Mexico using E3SM

Coastal ocean modeling is a high priority in the DOE‘s Energy Exascale Earth System Model (E3SM). The goal is to accurately predict the risk of damage to coastal resources and infrastructure due to a changing climate in the coming decades. North American coastal communities are areas of particular interest, as this fits under the topic of US national security and planning assessments in a changing climate. LANL Institutional Computing time for the Tier 1 allocation ”Coastal Ocean and Sea Ice Modeling” have been used for development and testing of numerical methods needed for E3SM coastal applications.

54 ENVIRONMENTAL SCIENCES↗

Comets

Vacuum ultraviolet observations from sounding rockets and satellite observatories of the gaseous comae of several comets are reviewed. The earliest of these led to discovery of the hydrogen envelope extending for millions of km from the nucleus. Subsequent observations of H I Lyman alpha, the OH (0,0 band and the oxygen resonance triplet provided strong evidence for the water-ice model of the cometary nucleus. Several species were discovered in the coma including C, C(+), CO, S, and CS. High resolution spectroscopy and the spatial variation of the observed emissions provide means to elucidate the production and excitation mechanisms of these species. The similarity of the spectra of the half dozen comets observed to date argues for a common, homogeneous composition (with the exception of dust and CO) of the cometary ice and a minimal effect on the neutral species due to molecular collisions in the inner coma.

Wilkening, L. L.↗