Properties Of Ice Particles Research Articles

Sensitivity of Convective Cell Dynamics and Microphysics to Model Resolution for the OWLeS IOP2b Lake-Effect Snowband

AbstractThe OWLeS IOP2b lake-effect case is simulated using the Weather Research and Forecasting (WRF) Model with a horizontal grid spacing of 148 m (WRF-LES mode). The dynamics and microphysics of the simulated high-resolution snowband and a coarser-resolution band from the parent nest (1.33-km horizontal grid spacing) are compared to radar and aircraft observations. The Ice Spheroids Habit Model with Aspect-ratio Evolution (ISHMAEL) microphysics is used, which predicts the evolution of ice particle properties including shape, maximum diameter, density, and fall speed. The microphysical changes within the band that occur when going from 1.33-km to 148-m grid spacing are explored. Improved representation of the dynamics at higher resolution leads to a better representation of the microphysics of the snowband compared to radar and aircraft observations. Stronger updrafts in the high-resolution grid produce higher ice number concentrations and produce ice particles that are more heavily rimed and thus more spherical, smaller (in terms of mean maximum diameter), and faster falling. These changes to the ice particle properties in the high-resolution grid limit the production of aggregates and improve reflectivity compared to observations. Graupel, observed in the band at the surface, is simulated in the strongest convective updrafts, but only at the higher resolution. Ultimately, the duration of heavy precipitation just onshore from the collapse of convection is better predicted in the high-resolution domain compared to surface and radar observations.

Microphysical properties and fall speed measurements of snow ice crystals using the Dual Ice Crystal Imager (D-ICI)

Abstract. Accurate predictions of snowfall require good knowledge of the microphysical properties of the snow ice crystals and particles. Shape is an important parameter as it strongly influences the scattering properties of the ice particles, and thus their response to remote sensing techniques such as radar measurements. The fall speed of ice particles is another important parameter for both numerical forecast models as well as representation of ice clouds and snow in climate models, as it is responsible for the rate of removal of ice from these models. We describe a new ground-based in situ instrument, the Dual Ice Crystal Imager (D-ICI), to determine snow ice crystal properties and fall speed simultaneously. The instrument takes two high-resolution pictures of the same falling ice particle from two different viewing directions. Both cameras use a microscope-like setup resulting in an image pixel resolution of approximately 4 µm pixel−1. One viewing direction is horizontal and is used to determine fall speed by means of a double exposure. For this purpose, two bright flashes of a light-emitting diode behind the camera illuminate the falling ice particle and create this double exposure, and the vertical displacement of the particle provides its fall speed. The other viewing direction is close-to-vertical and is used to provide size and shape information from single-exposure images. This viewing geometry is chosen instead of a horizontal one because shape and size of ice particles as viewed in the vertical direction are more relevant than these properties viewed horizontally, as the vertical fall speed is more strongly influenced by the vertically viewed properties. In addition, a comparison with remote sensing instruments that mostly have a vertical or close-to-vertical viewing geometry is favoured when the particle properties are measured in the same direction. The instrument has been tested in Kiruna, northern Sweden (67.8∘ N, 20.4∘ E). Measurements are demonstrated with images from different snow events, and the determined snow ice crystal properties are presented.

Ice Particle Properties Inferred from Aggregation Modelling

Ice Particle Properties Inferred from Aggregation Modelling

Influence of the Spectral Dependence of Refractive Index on the Polarimetric Properties of Ice Particles

Water ice is widespread in the Solar System. Computer simulation of light scattering by ice particles designed to interpret the observational data should take into account the spectral dependence of the refractive index of water ice. However, in practice, a single fixed value of the refractive index is often used. In this paper, we show that poor choice of a fixed refractive index commonly leads to significant errors in estimating both the intensity and the degree of polarization of single-scattered light. We have found that a fixed value of the refractive index of ice particles m0 = 1.3078 in the spectral region from 0.4 to 0.9 μm leads to minimal differences between the calculated characteristics of the light scattered by ice particles and those that take into account the spectral behavior of the refractive index. The most suitable values of the fixed refractive index for the widely used R, V, and I filters have been found. We have also studied the effect of the fixed refractive index of ice on the spectral dependence of the main parameters of the phase dependence of the linear polarization degree of single-scattered light, such as the magnitude and position of the minimum of the negative branch, the magnitude and position of the maximum of the positive branch, the inversion angle, and the polarimetric slope. The results of the calculations can be used to interpret the polarization of various objects of the Solar System that contain ice particles.

Modeling Radar Albedos of Laboratory‐Characterized Particles: Application to the Lunar Surface

AbstractWe analyze lunar images obtained by the Mini Radio Frequency instrument onboard the Lunar Reconnaissance Orbiter to interpret the anomalous radar scattering observed in some lunar craters. We compare the radar signatures of the crater floors to those of the regions external to the crater rim and show that there is a systematic difference between the radar albedo trends of the two regions. Using numerical simulations to compute radar scattering properties of rock and ice particles, we demonstrate that the difference is caused partly by the near‐surface bulk volume density or the underlying fine‐grained regolith and partly by the shape and size distributions of centimeter‐to‐decimeter‐scale rubble. We show that while the size distribution of wavelength‐scale particles plays the major role in the observed radar albedos, if the size distribution is fixed, the particle shapes can play a greater role than the composition; therefore, the icy material is indistinguishable from silicate‐rich material unless the abundance of ice in the particles plays a major role in the shape of the particles.

Sensitivity of Simulated Deep Convection to a Stochastic Ice Microphysics Framework

AbstractIce microphysics parameterizations in models must make major simplifications relative to observations, typically employing empirical relationships to represent average functional properties of particles. However, previous studies have established that ice particle properties vary even in similar cloud types and thermodynamic environments, and it remains unclear how this so‐called “natural variability” impacts simulated deep convection. This uncertainty is addressed by implementing a stochastic framework into the Predicted Particle Properties microphysics scheme in the Weather Research and Forecasting model. The approach stochastically varies the coefficients of the mass‐size (m‐D) relationship (m=aDb) for unrimed and partially rimed ice. Using guidance from aircraft in situ measurements obtained during the Midlatitude Continental Convective Clouds Experiment (MC3E), the scheme samples from distributions of the prefactor (a) and the exponent (b) of the m‐D relationship. Simulations of two MC3E deep convective cases indicate that the stochastic m‐D scheme produces considerable variability of anvil cirrus cloud optical depth (τ) distributions, even for the same ice water path (IWP). Thus, the stochastic scheme produces variable cloud radiative forcing that is independent of IWP. This τ‐IWP relationship variability is nonexistent using the deterministic m‐D ensemble. Additional sensitivity tests are performed in which the fallspeed‐size relationship (V=cDd) is stochastically varied, resulting in variable precipitation amounts and rain rate distributions. Results are presented in the context of satellite and precipitation observations and include comparison with other ensemble configurations using perturbed initial and lateral boundary conditions and small‐amplitude noise added to the potential temperature field.

Laboratory study of the properties of frazil ice particles and flocs in water of different salinities

Abstract. Measurements of the size and shape of frazil ice particles and flocs in saline water and of frazil ice flocs in freshwater are limited. This study consisted of a series of laboratory experiments producing frazil ice at salinities of 0 ‰, 15 ‰, 25 ‰ and 35 ‰ to address this lack of data. The experiments were conducted in a large tank in a cold room with bottom-mounted propellers to create turbulence. A high-resolution camera system was used to capture images of frazil ice particles and flocs passing through cross-polarizing lenses. The high-resolution images of the frazil ice were processed using a computer algorithm to differentiate particles from flocs and determine key properties including size, concentration and volume. The size and volume distributions of particles and flocs at all four salinities were found to fit log-normal distributions closely. The concentration, mean size, and standard deviation of flocs and particles were assessed at different times during the supercooling process to determine how these properties evolve with time. Comparisons were made to determine the effect of salinity on the properties of frazil ice particles and flocs. The overall mean size of frazil ice particles in saline water and freshwater was found to range between 0.52 and 0.45 mm, with particles sizes in freshwater ∼13 % larger than in saline water. However, qualitative observations showed that frazil ice particles in saline water tend to be more irregularly shaped. The overall mean size of flocs in freshwater was 2.57 mm compared to a mean size of 1.47 mm for flocs in saline water. The average growth rate of frazil particles was found to be 0.174, 0.070, 0.033, and 0.024 mm min−1 and the average floc growth rate was 0.408, 0.118, 0.089, and 0.072 mm min−1 for the 0 ‰, 15 ‰, 25 ‰, and 35 ‰, respectively. Estimates for the porosity of frazil ice flocs were made by equating the estimated volume of ice produced based on thermodynamic conditions to the estimated volume of ice determined from the digital images. The estimated porosities of frazil ice flocs were determined to be 0.86, 0.82, 0.8 and 0.75 for 0 ‰, 15 ‰, 25 ‰ and 35 ‰ saline water, respectively.

Effects of Ice Particle Representation on Passive Microwave Precipitation Retrieval in a Bayesian Scheme

A physically based Bayesian passive microwave precipitation retrieval requires an accurate forward radiative transfer model along with realistic database representation of hydrometeors, atmospheric properties, and surface emission. NASA’s Global Precipitation Measurement (GPM) Mission provides an unprecedented opportunity for the development of such databases, matching a well-calibrated radiometer with dual-frequency radar. Early versions of passive microwave products from GPM utilized a physically constructed database in a Bayesian retrieval scheme, assumed ice particles to be spheres, and used Mie radiative transfer. A large body of recent work demonstrates that this is insufficient for retrieval at the GPM radiometer frequencies. In this paper, the retrieval is updated to use nonspherical particles. Simulated brightness temperature (Tb) agreement with observations is shown to be significantly improved across the high frequencies, decreasing biases significantly and increasing correlations to observed Tb. This is compared with a second identical retrieval performed with the assumption of spherical ice particles, and retrieval results are compared globally, seasonally, and instantaneously for a case study at the rain rate level. While not at the high level of improvement shown in Tb space, the precipitation retrieval is improved as compared to one using observed Tb in correlation, bias, and root-mean-square error. Reported improvements, while modest in magnitude, advance the retrieval to more physical consistency which allows for deeper insight into ice particle properties associated with precipitation.

Theoretical and Experimental Study on Echo Fluctuation Suppression of a Cirrus Cloud by Millimeter Wave MIMO Radar

The scattering properties of nonspherical particles can be approximately computed by equivalent spherical theory. The scattering properties of ice particles were approximately computed by Rayleigh approximation because the sizes of the ice particles are smaller than the wavelength of millimeter wave radar. Based on the above assumption, the echo fluctuation of moving particles was analyzed by computing the total backscattering field of a cirrus cloud using the classical vector potential technique. The simulation results showed that echo fluctuation influences the accuracy of retrieving the physical parameters of a cloud. To suppress the echo fluctuation of moving ice particles, a video integrator of a millimeter wave cloud radar would be used. However, video integrators lose the rapidly changing information of ice particles and reduce radar range resolution; thus, we propose the pace-diversity technique of MIMO radar to reduce the echo fluctuation, which could be validated by theoretical computation and experimental measurements.

Arctic ice clouds over northern Sweden: microphysical properties studied with the Balloon-borne Ice Cloud particle Imager B-ICI

Abstract. Ice particle and cloud properties such as particle size, particle shape and number concentration influence the net radiation effect of cirrus clouds. Measurements of these features are of great interest for the improvement of weather and climate models, especially for the Arctic region. In this study, balloon-borne in situ measurements of Arctic cirrus clouds have been analysed for the first time with respect to their origin. Eight cirrus cloud measurements have been carried out in Kiruna (68∘ N), Sweden, using the Balloon-borne Ice Cloud particle Imager (B-ICI). Ice particle diameters between 10 and 1200 µm have been found and the shape could be recognized from 20 µm upwards. Great variability in particle size and shape is observed. This cannot simply be explained by local environmental conditions. However, if sorted by cirrus origin, wind and weather conditions, the observed differences can be assessed. Number concentrations between 3 and 400 L−1 have been measured, but the number concentration has reached values above 100 L−1 only for two cases. These two cirrus clouds are of in situ origin and have been associated with waves. For all other measurements, the maximum ice particle concentration is below 50 L−1 and for one in situ origin cirrus case only 3 L−1. In the case of in situ origin clouds, the particles are all smaller than 350 µm diameter. The PSDs for liquid origin clouds are much broader with particle sizes between 10 and 1200 µm. Furthermore, it is striking that in the case of in situ origin clouds almost all particles are compact (61 %) or irregular (25 %) when examining the particle shape. In liquid origin clouds, on the other hand, most particles are irregular (48 %), rosettes (25 %) or columnar (14 %). There are hardly any plates in cirrus regardless of their origin. It is also noticeable that in the case of liquid origin clouds the rosettes and columnar particles are almost all hollow.

Impacts of Ice Particle Shape and Density Evolution on the Distribution of Orographic Precipitation

Abstract An IMPROVE-2 orographic precipitation case is simulated using the Ice-Spheroids Habit Model with Aspect-Ratio Evolution (ISHMAEL) microphysics. In ISHMAEL, the evolution of ice particle properties such as mass, shape, size, density, and fall speed are predicted. These ice particle properties along with the ice size distributions from ISHMAEL and model-derived spatial distribution of accumulated precipitation are compared to observations. ISHMAEL predicts planar and columnar particles at spatial locations that agree with observations. Sensitivity simulations are used to explore the impact of predicting ice particle shape evolution on orographic cloud properties and precipitation compared to the traditional approach of representing snow and graupel using separate categories with conversion from snow to graupel during riming. High biases in both IWCs aloft and surface precipitation accumulation occur in the Umpqua River valley using separate snow and graupel categories because snow that does not convert to graupel is advected over the Coast Range and precipitates out in the valley. Improvements in IWCs aloft and surface precipitation using ISHMAEL occur from both predicting various vapor-grown habits and predicting the impact of partial riming on ice particle properties. Compared to traditional microphysics schemes, ISHMAEL also produces less spatial variability in accumulated precipitation.

Microphysical Characteristics of Squall-Line Stratiform Precipitation and Transition Zones Simulated Using an Ice Particle Property-Evolving Model

Abstract A quasi-idealized 3D squall-line case is simulated using a novel bulk microphysics scheme called the Ice-Spheroids Habit Model with Aspect-ratio Evolution (ISHMAEL). In ISHMAEL, the evolution of ice particle properties (e.g., mass, shape, maximum diameter, density, and fall speed) are predicted during vapor growth, sublimation, riming, and melting, allowing ice properties to evolve from various microphysical processes without needing separate unrimed and rimed ice categories. ISHMAEL produces both a transition zone and an enhanced stratiform precipitation region, and ice particle properties are analyzed to determine the characteristics of ice that lead to the development of these squall-line features. Rimed particles advected rearward from the convective region produce the enhanced stratiform precipitation region. The transition zone results from hydrometeor sorting; the evolution of ice particle properties in the convective region leads to fall speeds that favor ice advecting rearward of the transition zone before reaching the melting level, causing a local minimum in precipitation rate and reflectivity there. Sensitivity studies show that the fall speed of ice particles largely determines the location of the enhanced stratiform precipitation region and whether or not a transition zone forms. The representation of microphysical processes, such as rime splintering and aggregation, and ice size distribution shape can impact the mean ice particle fall speeds enough to significantly impact the location of the enhanced stratiform precipitation region and the existence of the transition zone.

PHIPS-HALO: the airborne particle habit imaging and polar scattering probe – Part 2: Characterization and first results

Abstract. The novel aircraft optical cloud probe PHIPS-HALO has been developed to establish clarity regarding the fundamental link between the microphysical properties of single atmospheric ice particles and their appropriated angular light scattering function. After final improvements were implemented in the polar nephelometer part and the acquisition software of PHIPS-HALO, the instrument was comprehensively characterized in the laboratory and was deployed in two aircraft missions targeting cirrus and Arctic mixed-phase clouds. This work demonstrates the proper function of the instrument under aircraft conditions and highlights the uniqueness, quality, and limitations of the data that can be expected from PHIPS-HALO in cloud-related aircraft missions.

Idealized Simulations of a Squall Line from the MC3E Field Campaign Applying Three Bin Microphysics Schemes: Dynamic and Thermodynamic Structure

The squall-line event on 20 May 2011, during the Midlatitude Continental Convective Clouds (MC3E) field campaign has been simulated by three bin (spectral) microphysics schemes coupled into the Weather Research and Forecasting (WRF) Model. Semi-idealized three-dimensional simulations driven by temperature and moisture profiles acquired by a radiosonde released in the preconvection environment at 1200 UTC in Morris, Oklahoma, show that each scheme produced a squall line with features broadly consistent with the observed storm characteristics. However, substantial differences in the details of the simulated dynamic and thermodynamic structure are evident. These differences are attributed to different algorithms and numerical representations of microphysical processes, assumptions of the hydrometeor processes and properties, especially ice particle mass, density, and terminal velocity relationships with size, and the resulting interactions between the microphysics, cold pool, and dynamics. This study shows that different bin microphysics schemes, designed to be conceptually more realistic and thus arguably more accurate than bulk microphysics schemes, still simulate a wide spread of microphysical, thermodynamic, and dynamic characteristics of a squall line, qualitatively similar to the spread of squall-line characteristics using various bulk schemes. Future work may focus on improving the representation of ice particle properties in bin schemes to reduce this uncertainty and using the similar assumptions for all schemes to isolate the impact of physics from numerics.

Evaluation of Cloud Microphysical Schemes for a Warm Frontal Snowband during the GPM Cold Season Precipitation Experiment (GCPEx)

Detailed observations from the Global Precipitation Measurement (GPM) mission Cold Season Precipitation Experiment (GCPEx) of an intense warm frontal band on 18 February 2012 were used to evaluate several bulk microphysical parameterizations within the NASA-Unified Weather Research and Forecasting (NU-WRF) Model. These included the Predicted Particle Properties (P3), Morrison (MORR), Stony Brook University (SBU), and Goddard four-class ice (4ICE) microphysics schemes. All schemes were able to predict the snowband, but the simulated intensities varied because of various assumptions in these schemes. The saturation adjustment scheme within MORR promoted excessive amounts of cloud water evaporational cooling in the warm sector, which contributed to a decrease in midlevel instability approaching the frontal band and thus a weaker band. In contrast, the explicit calculation of cloud water condensation/evaporation in the P3 scheme produced limited amounts of evaporational cooling, which allowed for greater midlevel instability to support band development. The P3 and SBU schemes produced moderate rime/graupel mass within the band that was confirmed by observations, while the MORR and 4ICE schemes drastically underpredicted the graupel mass. The high-density, fast-falling rimed particles in P3 underwent weak sublimation and melting, which helped promote a stronger horizontal temperature gradient and greater low-level instability along the frontal band compared to the other schemes. Overall, the schemes that use specified thresholds for converting between the predefined ice-phase categories of cloud ice, snow, and graupel had the most unrepresentative hydrometeor types. These results highlight the advantage of predicting ice particle properties and explicitly calculating cloud water condensation/evaporation in the P3 scheme.

A single ice approach using varying ice particle properties in global climate model microphysics

AbstractIce and mixed‐phase cloud representation and simulation in global climate models are challenging with large uncertainties and biases. Sharing similar growth paths, no distinct separation exists in nature between cloud ice and snow. Different from conventional microphysics schemes separating cloud ice from snow, a single prognostic category is used to represent the whole spectrum of solid hydrometeors. Instead of using fixed physical properties for separate ice classes, e.g., the mass, area, and fall velocity, we consider the particle shape and riming impacts on ice properties. This approach simplifies several ice‐related microphysical processes and eliminates the ambiguity and uncertainty associated with parameterizing cloud ice to snow conversion. The modifications were implemented in the Morrison‐Gettelman (MG08) scheme and tested in Community Atmosphere Model. Evaluation using single column simulations indicated that the new approach increased the ice water content (IWC) in high clouds during dry period, which is improved compared to available retrievals. Global atmospheric simulations using the new approach give an overall comparable mean climate with notable improvement in terms of clouds and their radiative forcing. Both longwave and shortwave cloud forcing are closer to observations due to more realistic IWC, liquid water content, and cloud top height. Furthermore, the new approach yields slightly better representation of mixed‐phase clouds when a smaller capacitance for nonspherical particles is used in the ice depositional growth parameterization. Overall, the physically based single‐ice approach is a promising direction for future GCM microphysics development given its simplified representation of microphysical processes and flexible description of ice particle properties.

Simulated Polarimetric Fields of Ice Vapor Growth Using the Adaptive Habit Model. Part II: A Case Study from the FROST Experiment

Abstract A new adaptive habit model (AHM) grows ice crystals through vapor deposition while evolving ice particle properties, including shape and effective density. The AHM provides an opportunity to investigate observed microphysical processes through the computation of polarimetric variables and corroboration with microphysical model output. This study is unique because the polarimetric scattering calculations are computed using predicted microphysical parameters rather than a priori assumptions that are imposed within the scattering calculations in the forward simulator, allowing for a more effective comparison to radar observations. Through the simulation of a case in the Front Range of the Rocky Mountains in Colorado using the Advanced Research version of the Weather Research and Forecasting Model, it is found that the AHM approximates ice mass, shape, cloud vertical structure, and temporal evolution as reflected through polarimetric quantities compared to observations. AHM reflectivity magnitudes are similar to those observed with radar and are an improvement over spherical ice crystal assumptions. Further analyses are completed to examine the effect of microphysical processes on the evolution of the differential reflectivity and specific differential phase, both of which are simulated using the AHM. Simulations reveal a polarimetric response to ice crystal mass, number, size, density, and aspect ratio. While results reveal the need for model improvements (e.g., parameterizations for aggregation rate), testing forward-simulated radar fields against observations is a first step in the validation of model microphysical and precipitation processes.

Simulated Polarimetric Fields of Ice Vapor Growth Using the Adaptive Habit Model. Part I: Large-Eddy Simulations

Abstract The bulk adaptive habit model (AHM) explicitly predicts ice particle aspect ratio, improving the representation of microphysical processes and properties, including ice–liquid-phase partitioning. With the unique ability to predict ice particle shape and density, the AHM is combined with an offline forward operator to produce fields of simulated polarimetric variables. An evaluation of AHM-forward-simulated dual-polarization radar signatures in an idealized Arctic mixed-phase cloud is presented. Interpretations of those signatures are provided through microphysical model output using the large-eddy simulation mode of the Weather Research and Forecasting Model. Vapor-grown ice properties are associated with distinct observable signatures in polarimetric radar variables, with clear sensitivities to the simulated ice particle properties, including ice number, size, and distribution shape. In contrast, the liquid droplet number has little influence on both polarimetric and microphysical variables in the case presented herein. Polarimetric quantities are sensitive to the dominating crystal habit type in a volume, with enhancements for aspect ratios much lower or higher than unity. This synthesis of a microphysical model and a polarimetric forward simulator is a first step in the evaluation of detailed AHM microphysics.

Improvements in Global Climate Model Microphysics Using a Consistent Representation of Ice Particle Properties

AbstractThis paper describes a new approach for representing ice microphysics in climate models. In contrast with most previous schemes, this approach does not include separate categories for cloud and precipitating ice and instead uses a single two-moment category to represent all solid hydrometeors. Thus, there is no need for an ice “autoconversion” size threshold parameter, which has a critical impact on simulated climate in the Community Atmosphere Model (CAM5) yet is poorly constrained by theory or observations. Further, in the new treatment, all ice microphysical processes and parameters, including ice effective radius and mean fall speed, are formulated self-consistently and flexibly based on empirical ice particle mass–size and projected area–size relationships. This means that the scheme can represent the physical coupling between bulk particle density, mean fall speed, and effective radius, which is not possible in current schemes. Two different methods for specifying these relationships based on observations are proposed. The new scheme is tested in global simulations using CAM5. Differences in simulations using the two methods for specifying the mass– and projected area–size relationships, particularly the cloud radiative forcing, are attributable mainly to the effects on mean ice particle fall speed, impacting sedimentation and ice water path. With some tuning of parameters involved in calculating homogeneous freezing it produces a similar climate compared to the simulations using the original CAM5 microphysics. Thus, it can produce a comparable climate while improving the physical basis and self-consistency of ice particle properties and parameters.

Single-scattering properties of ice particles in the microwave regime: Temperature effect on the ice refractive index with implications in remote sensing

An ice crystal single-scattering property database is developed in the microwave spectral region (1 to 874GHz) to provide the scattering, absorption, and polarization properties of 12 ice crystal habits (10-plate aggregate, 5-plate aggregate, 8-column aggregate, solid hexagonal column, hollow hexagonal column, hexagonal plate, solid bullet rosette, hollow bullet rosette, droxtal, oblate spheroid, prolate spheroid, and sphere) with particle maximum dimensions from 2µm to 10mm. For each habit, four temperatures (160, 200, 230, and 270K) are selected to account for temperature dependence of the ice refractive index. The microphysical and scattering properties include projected area, volume, extinction efficiency, single-scattering albedo, asymmetry factor, and six independent nonzero phase matrix elements (i.e. P11, P12, P22, P33, P43 and P44). The scattering properties are computed by the Invariant Imbedding T-Matrix (II-TM) method and the Improved Geometric Optics Method (IGOM). The computation results show that the temperature dependence of the ice single-scattering properties in the microwave region is significant, particularly at high frequencies. Potential active and passive remote sensing applications of the database are illustrated through radar reflectivity and radiative transfer calculations. For cloud radar applications, ignoring temperature dependence has little effect on ice water content measurements. For passive microwave remote sensing, ignoring temperature dependence may lead to brightness temperature biases up to 5K in the case of a large ice water path.