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Hybrid (PDE+ML) models in the context of land ice modeling
Focal Area(s): Primary focal areas are: predictive modeling through the use of AI-derived model components; advanced methods including network design/optimization/deep learning. Science Challenge: The atmospheric, ocean and ice dynamics components of the Energy Exascale Earth System Model (E3SM) are governed by Partial Differential Equations (PDEs) and significant efforts have been made during the last decades to develop such computational models. Here we propose to fundamentally improve these PDE-based codes by enhancing them with Machine Learning (ML) sub-models for complex, poorly understood physical processes in the context of ice sheet modeling. We propose to train these models with a novel approach that allows the assimilation of the different sources of data available (direct/indirect observations and possibly simulation data), improving on existing simplified models. We also highlight computational challenges originating from the coexistence of PDE-based and ML-based models.
Nonlinear Insolation Forcing: A Physical Mechanism for Climate Change
This paper focuses on recent advances in the understanding of nonlinear insolation forcing for climate change. The amplitude-frequency resonances in the insolation variations induced by the Earth's changing obliquity are emergent and may provide a physical mechanism to drive the glaciation cycles. To establish the criterion that nonlinear insolation forcing is responsible for major climate changes, the cooperative phenomena between the frequency and amplitude of the insolation are defined as insolation pulsation. Coupling of the insolation frequency and amplitude variations has established an especially new and interesting series of insolation pulses. These pulses would modulate the insolation in such a way that the mode of insolation variations could be locked to generate the 100-kyr ice age cycle which is a long-time geophysical puzzle. The nonlinear behavior of insolation forcing is tested by energy balance and ice sheet climate models and the physical mechanism behind this forcing is explained in terms of pulse duration in the incoming solar radiation. Calculations of the solar energy flux at the top of the atmosphere show that the duration of the negative and positive insolation pulses is about 2 thousand years which is long enough to prolong glaciation into deep ice ages and cause rapid melting of large ice sheets in the high latitudes of the northern hemisphere. We have performed numerical simulations of climate response to nonlinear insolation forcing for the past 2 million years. Our calculated results of temperature fluctuations are in good agreement with the climate cycles as seen in the terrestrial biogenic silica (BDP-96-2) data as well as in the marine oxygen isotope (delta(sup 18)O) records.
Introduction to the Glenn Icing Computational Environment (GlennICE)
The NASA John H. Glenn Research Center at Lewis Field is developing the Glenn Icing Computational Environment (GlennICE) tool to aid those evaluating, designing and certifying aircraft, engines, and aircraft components for flight in icing conditions. This short course will walk through some of the underlying physics involved with GlennICE and how we achieve efficient 3D ice accretion predictions. After an introduction of GlennICE, an analysis of the Common Research Model High-Lift will be demonstrated to showcase the typical workflow for an aircraft icing analysis. Within this walkthrough, capabilities will be highlighted with future planned capabilities being discussed. Finally, we will showcase the impact GlennICE is having on NASA’s icing portfolio and how it is advancing aircraft icing research and safety.
Arctic Aerosol Sources and Mixing States Field Campaign Report
The Arctic is warming at a faster rate than anywhere else on Earth, with rapidly shrinking sea ice extent transforming the region. Depending on chemical and physical properties, atmospheric aerosols directly scatter and/or absorb radiation, serve as cloud droplet and/or ice crystal nuclei, and/or reduce the reflectiveness of the snow surface, thereby altering the atmospheric energy budget. There is a wide spread in the magnitude of simulated arctic aerosol radiative forcing, and significant differences in aerosol concentration levels and seasonal cycles often exist between models and observations. Increasing local natural and anthropogenic emissions are significant, with uncertain climate impacts due to complex feedbacks. Model evaluations, however, are limited by the dearth of arctic aerosol observations available and an inadequate understanding of arctic aerosol processes. The majority of previous arctic aerosol observations have been made through intensive spring/summer field campaigns, with few intensive measurement studies focused on the fall-winter transition, a period when freeze-up is occurring later and thinning sea ice is resulting in wintertime ice fracturing. Aerosol monitoring at arctic coastal stations has provided knowledge of long-term seasonal trends in aerosol concentrations. The completed ARM field campaign addresses observational and knowledge gaps through detailed aerosol size and chemical composition measurements during the fall-winter transition in the coastal Arctic and through the entire annual cycle in the central Arctic. The observations are improving our understanding of the sources and processes controlling the aerosol population in the rapidly changing Arctic.
Validation Results for LEWICE 3.0
A research project is underway at NASA Glenn to produce computer software that can accurately predict ice growth under any meteorological conditions for any aircraft surface. This report will present results from version 3.0 of this software, which is called LEWICE. This version differs from previous releases in that it incorporates additional thermal analysis capabilities, a pneumatic boot model, interfaces to computational fluid dynamics (CFD) flow solvers and has an empirical model for the supercooled large droplet (SLD) regime. An extensive comparison of the results in a quantifiable manner against the database of ice shapes and collection efficiency that have been generated in the NASA Glenn Icing Research Tunnel (IRT) has also been performed. The complete set of data used for this comparison will eventually be available in a contractor report. This paper will show the differences in collection efficiency between LEWICE 3.0 and experimental data. Due to the large amount of validation data available, a separate report is planned for ice shape comparison. This report will first describe the LEWICE 3.0 model for water collection. A semi-empirical approach was used to incorporate first order physical effects of large droplet phenomena into icing software. Comparisons are then made to every single element two-dimensional case in the water collection database. Each condition was run using the following five assumptions: 1) potential flow, no splashing; 2) potential flow, no splashing with 21 bin drop size distributions and a lift correction (angle of attack adjustment); 3) potential flow, with splashing; 4) Navier-Stokes, no splashing; and 5) Navier-Stokes, with splashing. Quantitative comparisons are shown for impingement limit, maximum water catch, and total collection efficiency. The results show that the predicted results are within the accuracy limits of the experimental data for the majority of cases.
Contact Freezing of Water Droplets by Crystalline Organic Acids
The ability of water to freeze into ice crystals in mixed-phase clouds affects physical properties, including particle size, precipitation rates, and radiative properties. The presence of an insoluble particle at the surface of water droplets can promote ice nucleation at temperatures higher than that of pure water, even in the absence of a collision. However, contact freezing remains an underexplored mode of ice nucleation. Here, we present a study of atmospherically relevant organic acids and their role as effective ice-nucleating particles (INP) in contact mode using a Raman-microscope-equipped environmental chamber. We determined contact freezing temperatures induced by solid crystals of docosanol, adipic acid, cis-pinonic acid, fumaric acid, 4-hydroxybenzoic acid, palmitic acid, phthalic acid, sebacic acid, stearic acid, terephthalic acid, and vanillic acid. All solids except fumaric acid promoted contact freezing of water droplets at significantly higher temperatures than pure water in the chamber (−15.0 to −18.5 °C vs −21.3 °C). Physical and chemical properties were identified which correlate with greater effectiveness of INPs in the contact mode, including crystal lattice mismatch with ice, carbon number, and insolubility in water. In conclusion, we suggest that the presence of these organic solids in atmospheric aerosols may promote atmospheric ice nucleation at warm temperatures.
Atmospheric Rotational Effects on Mars Based on the NASA Ames General Circulation Model: Angular Momentum Approach
The objective of the investigation is to determine the motion of the rotational axis of Mars as a result of mass variations in the atmosphere and condensation and sublimation of CO2 ice on the polar caps. A planet experiences this type of motion if it has an atmosphere, which is changing its mass distribution with respect to the solid body of the planet and/or it is asymmetrically changing the amount of ice at the polar caps. The physical principle involved is the conservation of angular momentum, one can get a feeling for it by sitting on a well oiled swivel chair holding a rotating wheel on a horizontal direction and then changing the rotation axis of the wheel to a vertical direction. The person holding the wheel and the chair would begin to rotate in opposite direction to the rotation of the wheel. The motions of Mars atmosphere and the ice caps variations are obtained from a mathematical model developed at the NASA Ames Research Center. The model produces outputs for a time span of one Martian year, which is equivalent to 687 Earth days. The results indicate that Mars axis of rotation moves in a spiral with respect to a reference point on the surface of the planet. It can move as far away as 35.3 cm from the initial location as a result of both mass variations in the atmosphere and asymmetric ice variations at the polar caps. Furthermore the pole performs close to two revolutions around the reference point during a Martian year. This motion is a combination of two motions, one produced by the atmospheric mass variations and another due to the variations in the ice caps. The motion due to the atmospheric variations is a spiral performing about two and a half revolutions around the reference point during which the pole can move as far as 40.9 cm. The motion due to variations in the ice caps is a spiral performing almost three revolutions during which the pole can move as far as 32.8 cm.
Latest Developments in SLD Scaling
Scaling methods have been shown previously to work well for super cooled large droplet (SLD) main ice shapes. However, feather sizes for some conditions have not been well represented by scale tests. To determine if there are fundamental differences between the development of feathers for appendix C and SLD conditions, this study used time-sequenced photographs, viewing along the span of the model during icing sprays. An airspeed of 100 kt, cloud water drop MVDs of 30 and 140 microns, and stagnation freezing fractions of 0.30 and 0.50 were tested in the NASA Glenn Icing Research Tunnel using an unswept 91-cm-chord NACA0012 airfoil model mounted at 0deg AOA. The photos indicated that the feathers that developed in a distinct region downstream of the leading-edge ice determined the horn location and angle. The angle at which feathers grew from the surface were also measured; results are shown for an airspeed of 150 kt, an MVD of 30 microns, and stagnation freezing fractions of 0.30 to 0.60. Feather angles were found to depend strongly on the stagnation freezing fraction, and were independent of either chordwise position on the model or time into the spray. Feather angles also correlated well with horn angles. For these tests, there did not appear to be fundamental differences between the physics of SLD and appendix C icing; therefore, for these conditions similarity parameters used for appendix C scaling appear to be valid for SLD scaling as well. Further investigation into the cause for the large feather structures observed for some SLD conditions will continue.
Further Refinement of the LEWICE SLD Model
A research project is underway at NASA Glenn Research Center to produce computer software that can accurately predict ice growth for any meteorological conditions for any aircraft surface. This report will present results from version 3.2 of this software, which is called LEWICE. This version differs from previous releases in that it incorporates additional thermal analysis capabilities, a pneumatic boot model, interfaces to external computational fluid dynamics (CFD) flow solvers and has an empirical model for the supercooled large droplet (SLD) regime. An extensive comparison against the database of ice shapes and collection efficiencies that have been generated in the NASA Glenn Icing Research Tunnel (IRT) has also been performed. The complete set of data used for this comparison will eventually be available in a contractor report. This paper will show the differences in collection efficiency and ice shape between LEWICE 3.2 and experimental data. This report will first describe the LEWICE 3.2 SLD model. A semi-empirical approach was used to incorporate first order physical effects of large droplet phenomena into icing software. Comparisons are then made to every two-dimensional case in the water collection database and the ice shape database. Each collection efficiency condition was run using the following four assumptions: 1) potential flow, no splashing; 2) potential flow, with splashing; 3) Navior-Stokes, no splashing; 4) Navi r-Stokes, with splashing. All cases were run with 21 bin drop size distributions and a lift correction (angle of attack adjustment). Quantitative comparisons are shown for impingement limit, maximum water catch, and total collection efficiency. Due to the large number of ice shape cases, comprehensive comparisons were limited to potential flow cases with and without splashing. Quantitative comparisons are shown for horn height, horn angle, icing limit, area, and leading edge thickness. The results show that the predicted results for both ice shape and water collection are within the accuracy limits of the experimental data for the majority of cases.
Implications of Aerosol Physicochemical Properties Including Ice Nucleation at ARM Mega Sites for Improved Understanding of Microphysical Atmospheric Cloud Processes (Final Technical Report)
Continuous, long-term measurements of atmospheric ice-nucleating particles (INPs) that influence clouds and precipitation were conducted to investigate the abundance and variability of ground-level INPs across the world. Three field campaigns were organized by the DOE Atmospheric Radiation Measurement (ARM) program, including Examining INP from Southern Great Plains (ExINP-SGP, 2019), Examining INP from Eastern North Atlantic (ExINP-ENA, 2020 – 2021), and Examining INP from North Slope of Alaska (ExINP-NSA, 2021 – 2024). Additional small-scale supporting field experiments were performed in 2019 and 2021 to collect airborne particulate matter at SGP for complementary laboratory characterization of the particles’ physical and chemical properties [Aerosol-Ice Formation Closure Pilot Study (AEROICESTUDY), 2019; ExINP-SGP II, 2021]. In these studies, the PI’s team measured INP concentration with both real-time and laboratory measurements in a wide range of freezing temperatures ($T$ from 0 °C to about –30 °C). This project elucidated spatial variability and seasonality in the abundance of immersion mode active INPs across three ARM sites using a single instrument, a Portable Ice Nucleation Experiment (PINE) chamber version 03 (PINE-03 hereafter). Collocated aerosol and meteorological data were analyzed to assess the correlation between ambient INP abundance, air mass origin region, and meteorological variability. Our findings suggest very high freezing efficiency of INPs at the NSA site across the measured temperatures (ice nucleation active surface site density, $n_s(T)$, $\approx 2 \times 10^{8} - 10^{10}$ m -2 for from –16 to –31 °C), which is a factor of 10 – 1000 times greater efficiency as compared to that found in the previous mid-latitude INP measurements in autumn using the same instrument; surprisingly high INP abundance ($\ge 1 \text{ L}^{-1}$ at –25 °C) for the examined temperatures throughout the year that PINE-03 did not measure at other sites; and high INP concentration in spring, possibly related to arctic haze episodes.
Molecular dynamics of the water liquid-vapor interface
The results of molecular dynamics calculations on the equilibrium interface between liquid water and its vapor at 325 K are presented. For the TIP4P model of water intermolecular pair potentials, the average surface dipole density points from the vapor to the liquid. The most common orientations of water molecules have the C2 nu molecular axis roughly parallel to the interface. The distributions are quite broad and therefore compatible with the intermolecular correlations characteristic of bulk liquid water. All near-neighbor pairs in the outermost interfacial layers are hydrogen bonded according to the common definition adopted here. The orientational preferences of water molecules near a free surface differ from those near rigidly planar walls which can be interpreted in terms of patterns found in hexagonal ice 1. The mean electric field in the interfacial region is parallel to the mean polarization which indicates that attention cannot be limited to dipolar charge distributions in macroscopic descriptions of the electrical properties of this interface. The value of the surface tension obtained is 132 +/- 46 dyn/cm, significantly different from the value for experimental water of 68 dyn/cm at 325 K.
Carbon Dioxide Removal via Passive Thermal Approaches
A paper describes a regenerable approach to separate carbon dioxide from other cabin gases by means of cooling until the carbon dioxide forms carbon dioxide ice on the walls of the physical device. Currently, NASA space vehicles remove carbon dioxide by reaction with lithium hydroxide (LiOH) or by adsorption to an amine, a zeolite, or other sorbent. Use of lithium hydroxide, though reliable and well-understood, requires significant mass for all but the shortest missions in the form of lithium hydroxide pellets, because the reaction of carbon dioxide with lithium hydroxide is essentially irreversible. This approach is regenerable, uses less power than other historical approaches, and it is almost entirely passive, so it is more economical to operate and potentially maintenance- free for long-duration missions. In carbon dioxide removal mode, this approach passes a bone-dry stream of crew cabin atmospheric gas through a metal channel in thermal contact with a radiator. The radiator is pointed to reject thermal loads only to space. Within the channel, the working stream is cooled to the sublimation temperature of carbon dioxide at the prevailing cabin pressure, leading to formation of carbon dioxide ice on the channel walls. After a prescribed time or accumulation of carbon dioxide ice, for regeneration of the device, the channel is closed off from the crew cabin and the carbon dioxide ice is sublimed and either vented to the environment or accumulated for recovery of oxygen in a fully regenerative life support system.
Phase Equilibrium of Water with Hexagonal and Cubic Ice Using the SCAN Functional
Machine learning models are rapidly becoming widely used to simulate complex physicochemical phenomena with ab initio accuracy. Here, we use one such model as well as direct density functional theory (DFT) calculations to investigate the phase equilibrium of water, hexagonal ice (Ih), and cubic ice (Ic), with an eye toward studying ice nucleation. The machine learning model is based on deep neural networks and has been trained on DFT data obtained using the SCAN exchange and correlation functional. We use this model to drive enhanced sampling simulations aimed at calculating a number of complex properties that are out of reach of DFT-driven simulations and then employ an appropriate reweighting procedure to compute the corresponding properties for the SCAN functional. This approach allows us to calculate the melting temperature of both ice polymorphs, the driving force for nucleation, the heat of fusion, the densities at the melting temperature, the relative stability of ices Ih and Ic, and other properties. We find a correct qualitative prediction of all properties of interest. In some cases, quantitative agreement with experiment is better than for state-of-the-art semiempirical potentials for water. Furthermore, our results also show that SCAN correctly predicts that ice Ih is more stable than ice Ic.
Eddy transport of water vapor in the Martian atmosphere
Viking orbiter measurements of the Martian atmosphere suggest that the residual north polar water-ice cap is the primary source of atmospheric water vapor, which appears at successively lower northern latitudes as the summer season progresses. Zonally symmetric studies of water vapor transport indicate that the zonal mean meridional circulation is incapable of transporting from north polar regions to low latitudes the quantity of water vapor observed. This result has been interpreted as implying the presence of nonpolar sources of water. Another possibility is the ability of atmospheric wave motions, which are not accounted for in a zonally symmetric framework, to efficiently accomplish the transport from a north polar source to the entirety of the Northern Hemisphere. The ability or inability of the full range of atmospheric motions to accomplish this transport has important implications regarding the questions of water sources and sinks on Mars: if the full spectrum of atmospheric motions proves to be incapable of accomplishing the transport, it strengthens arguments in favor of additional water sources. Preliminary results from a three dimensional atmospheric dynamical/water vapor transport numerical model are presented. The model accounts for the physics of a subliming water-ice cap, but does not yet incorporate recondensation of this sublimed water. Transport of vapor away from this water-ice cap in this three dimensional framework is compared with previously obtained zonally symmetric (two dimensional) results to quantify effects of water vapor transport by atmospheric eddies.
Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data: Algorithm development and application
One essential parameter used in the estimation of radiative and turbulent heat fluxes from satellite data is surface temperature. Sea and land surface temperature (SST and LST) retrieval algorithms that utilize the thermal infrared portion of the spectrum have been developed, with the degree of success dependent primarily upon the variability of the surface and atmospheric characteristics. However, little effort has been directed to the retrieval of the sea ice surface temperature (IST) in the Arctic and Antarctic pack ice or the ice sheet surface temperature over Antarctica and Greenland. The reason is not one of methodology, but rather our limited knowledge of atmospheric temperature, humidity, and aerosol vertical, spatial and temporal distributions, the microphysical properties of polar clouds, and the spectral characteristics of snow, ice, and water surfaces. Over the open ocean the surface is warm, dark, and relatively homogeneous. This makes SST retrieval, including cloud clearing, a fairly straightforward task. Over the ice, however, the surface within a single satellite pixel is likely to be highly heterogeneous, a mixture of ice of various thicknesses, open water, and snow cover in the case of sea ice. Additionally, the Arctic is cloudy - very cloudy - with typical cloud cover amounts ranging from 60-90 percent. There are few observations of cloud cover amounts over Antarctica. The goal of this research is to increase our knowledge of surface temperature patterns and magnitudes in both polar regions, by examining existing data and improving our ability to use satellite data as a monitoring tool. Four instruments are of interest in this study: the AVHRR, ATSR, SMMR, and SSM/I. Our objectives are as follows. Refine the existing AVHRR retrieval algorithm defined in Key and Haefliger (1992; hereafter KH92) and applied elsewhere. Develop a method for IST retrieval from ATSR data similar to the one used for SST. Further investigate the possibility of estimating surface temperature from passive microwave data (in conjunction with AVHRR clear sky samples) through the use of 'effective emissivities' and physical relationships between skin temperature and subsurface temperature. Use the general method outlined in MK93 to calculate a 12-year record of clear sky equivalent surface temperatures, or possibly all-sky snow-ice interface physical temperatures, from SMMR and SSM/I, compare these temperatures to climatologies, ECMWF modeled surface temperatures, and surface temperatures predicted by a 2-D ice model. And intercompare several ice surface retrieval methods and validate them against ground measurements from the Swiss Camp on the Greenland ice sheet. Additionally, we intend to develop a surface temperature product based on AVHRR data and possibly blended with drifting buoy and meteorological station temperatures.
Near-Real-Time Satellite Cloud Products for Icing Detection and Aviation Weather over the USA
A set of physically based retrieval algorithms has been developed to derive from multispectral satellite imagery a variety of cloud properties that can be used to diagnose icing conditions when upper-level clouds are absent. The algorithms are being applied in near-real time to the Geostationary Operational Environmental Satellite (GOES) data over Florida, the Southern Great Plains, and the midwestern USA. The products are available in image and digital formats on the world-wide web. The analysis system is being upgraded to analyze GOES data over the CONUS. Validation, 24-hour processing, and operational issues are discussed.
Passive microwave studies of frozen lakes
Lakes of various sizes, depths and ice thicknesses in Alaska, Utah and Colorado were overflown with passive microwave sensors providing observations at several wavelengths. A layer model is used to calculate the microwave brightness temperature, T sub B (a function of the emissivity and physical temperatures of the object), of snowcovered ice underlain with water. Calculated T sub B's are comparable to measured T sub B's. At short wavelengths, e.g., 0.8 cm, T sub B data provide information on the near surface properties of ice covered lakes where the long wavelength, 21.0 cm, observations sense the entire thickness of ice including underlying water. Additionally, T sub B is found to increase with ice thickness. 1.55 cm observations on Chandalar Lake in Alaska show a T sub B increase of 38 K with an approximate 124 cm increase in ice thickness.