Ice Mass Density Research Articles

Current Status and Variation since 1964 of the Glaciers around the Ebi Lake Basin in the Warming Climate

This work analyzed the spatial and temporal variations of the glaciers in the Ebi Lake basin during the period 1964 to 2019, based on the 1st and 2nd Chinese Glacier Inventories (CGI) and remote sensing data; this is believed to be the first long-term comprehensive remote sensing investigation on the glacier change in this area, and it also diagnosed the response of the glaciers to the warming climate by analyzing digital elevation modeling and meteorology. The results show that there are 988 glaciers in total in the basin, with a total area of 560 km2 and average area of 0.57 km2 for a single glacier. The area and number of the glaciers oriented north and northeast are 205 km2 (327 glaciers) and 180 km2 (265 glaciers), respectively. The glaciers are categorized into eight classes as per their area, which are less than 0.1, 0.1–0.5, 0.5–1.0, 1.0–2.0, 2.0–5.0, 5.0–10.0, 10.0–20.0, and greater than 20.0 km2, respectively. The smaller glaciers between 0.1 km2 and 10.0 km2 account for 509 km2 or 91% in total area, and, in particular, the glaciers smaller than 0.5 km2 account for 74% in the total number. The glacial area is concentrated at 3500–4000 m in altitude (512 km2 or 91.4% in total). The number of glaciers in the basin decreased by 10.5% or 116, and their area decreased by 263.29 km2 (−4.79 km2 a−1) or 32% (−0.58% a−1) from 1964 to 2019; the glaciers with an area between 2.0 km2 and 5.0 km2 decreased by the largest, −82.60 km2 or −40.67% in the total area at −1.50 km2 a−1 or −0.74% a−1), and the largest decrease in number (i.e., 126 glaciers) occurs between 0.1 km2 and 0.5 km2. The total ice storage in the basin decreased by 97.84–153.22 km3 from 1964 to 2019, equivalent to 88.06–137.90 km3 water (taking 0.9 g cm−3 as ice mass density). The temperature increase rate in the basin was +0.37 °C decade−1, while the precipitation was +13.61 mm decade−1 during the last fifty-five years. This analysis shows that the increase in precipitation in the basin was not sufficient to compensate the mass loss of glaciers caused by the warming during the same period. The increase in temperature was the dominant factor exceeding precipitation mass supply for ruling the retreat of the glaciers in the entire basin.

Common volume satellite studies of polar mesospheric clouds with Odin/OSIRIS tomography and AIM/CIPS nadir imaging

Abstract. Two important approaches for satellite studies of polar mesospheric clouds (PMCs) are nadir measurements adapting phase function analysis and limb measurements adapting spectroscopic analysis. Combining both approaches enables new studies of cloud structures and microphysical processes but is complicated by differences in scattering conditions, observation geometry and sensitivity. In this study, we compare common volume PMC observations from the nadir-viewing Cloud Imaging and Particle Size (CIPS) instrument on the Aeronomy of Ice in the Mesosphere (AIM) satellite and a special set of tomographic limb observations from the Optical Spectrograph and InfraRed Imager System (OSIRIS) on the Odin satellite performed over 18 d for the years 2010 and 2011 and the latitude range 78 to 80∘ N. While CIPS provides preeminent horizontal resolution, the OSIRIS tomographic analysis provides combined horizontal and vertical PMC information. This first direct comparison is an important step towards co-analysing CIPS and OSIRIS data, aiming at unprecedented insights into horizontal and vertical cloud processes. Important scientific questions on how the PMC life cycle is affected by changes in humidity and temperature due to atmospheric gravity waves, planetary waves and tides can be addressed by combining PMC observations in multiple dimensions. Two- and three-dimensional cloud structures simultaneously observed by CIPS and tomographic OSIRIS provide a useful tool for studies of cloud growth and sublimation. Moreover, the combined CIPS/tomographic OSIRIS dataset can be used for studies of even more fundamental character, such as the question of the assumption of the PMC particle size distribution. We perform the first thorough error characterization of OSIRIS tomographic cloud brightness and cloud ice water content (IWC). We establish a consistent method for comparing cloud properties from limb tomography and nadir observations, accounting for differences in scattering conditions, resolution and sensitivity. Based on an extensive common volume and a temporal coincidence criterion of only 5 min, our method enables a detailed comparison of PMC regions of varying brightness and IWC. However, since the dataset is limited to 18 d of observations this study does not include a comparison of cloud frequency. The cloud properties of the OSIRIS tomographic dataset are vertically resolved, while the cloud properties of the CIPS dataset is vertically integrated. To make these different quantities comparable, the OSIRIS tomographic cloud properties cloud scattering coefficient and ice mass density (IMD) have been integrated over the vertical extent of the cloud to form cloud albedo and IWC of the same quantity as CIPS cloud products. We find that the OSIRIS albedo (obtained from the vertical integration of the primary OSIRIS tomography product, cloud scattering coefficient) shows very good agreement with the primary CIPS product, cloud albedo, with a correlation coefficient of 0.96. However, OSIRIS systematically reports brighter clouds than CIPS and the bias between the instruments (OSIRIS – CIPS) is 3.4×10-6 sr−1 (±2.9×10-6 sr−1) on average. The OSIRIS tomography IWC (obtained from the vertical integration of IMD) agrees well with the CIPS IWC, with a correlation coefficient of 0.91. However, the IWC reported by OSIRIS is lower than CIPS, and we quantify the bias to −22 g km−2 (±14 g km−2) on average.

A new description of probability density distributions of polar mesospheric clouds

Abstract. In this paper we present a new description of statistical probability density functions (pdfs) of polar mesospheric clouds (PMCs). The analysis is based on observations of maximum backscatter, ice mass density, ice particle radius, and number density of ice particles measured by the ALOMAR Rayleigh–Mie–Raman lidar for all PMC seasons from 2002 to 2016. From this data set we derive a new class of pdfs that describe the statistics of PMC events that is different from previous statistical methods using the approach of an exponential distribution commonly named the g distribution. The new analysis describes successfully the probability distributions of ALOMAR lidar data. It turns out that the former g-function description is a special case of our new approach. In general the new statistical function can be applied to many kinds of different PMC parameters, e.g., maximum backscatter, integrated backscatter, ice mass density, ice water content, ice particle radius, ice particle number density, or albedo measured by satellites. As a main advantage the new method allows us to connect different observational PMC distributions of lidar and satellite data, and also to compare with distributions from ice model studies. In particular, the statistical distributions of different ice parameters can be compared with each other on the basis of a common assessment that facilitates, for example, trend analysis of PMC.

The lunar semidiurnal tide at the polar summer mesopause observed by SOFIE

The polar summer mesopause, particularly the presence of noctilucent clouds (NLCs), exhibits pronounced temporal variability. Parts of this variability are thought to be caused by lunar tidal influences. We extract the semidiurnal lunar tide in various NLC related parameters by applying the superposed epoch analysis method to the dataset of the SOFIE satellite instrument. Analyzing the NLC seasons from 2007 to 2015 in the northern and southern hemisphere we, first, confirm the influence of the lunar tide on ice water content (IWC) and temperature. For both parameters the lunar influence had already recently been demonstrated in satellite measurements. Second, we apply the analysis to the variety of parameters observed by SOFIE including trace gases (H2O, O3, CH4, and NO), NLC properties (e.g., NLC altitudes and ice mass density), microphysical properties (e.g., particle concentration and mean radius), and mesopause properties. In all of these parameters we find signatures of the semidiurnal lunar tide, which is the first demonstration of this effect for all of these parameters. We quantify the lunar influence in terms of amplitudes and phases. Whereas the focus of the present study is providing observational evidence for the existence of lunar tidal signatures in various parameters, we do not aim at investigating the underlying mechanisms in detail, which is only possible with the utilization of comprehensive modeling approaches. Nevertheless, we briefly discuss the relations to known processes of the NLC evolution where appropriate, e.g., the relevance of the freeze-drying effect for the signature in H2O and the relation of IWC and NLC altitudes.

Exploring noctilucent cloud variability using the nudged and extended version of the Canadian Middle Atmosphere Model

Ice particles in the summer mesosphere – such as those connected to noctilucent clouds and polar mesospheric summer echoes - have since their discovery contributed to the uncovering of atmospheric processes on various scales ranging from interactions on molecular levels to global scale circulation patterns. While there are numerous model studies on mesospheric ice microphysics and how the clouds relate to the background atmosphere, there are at this point few studies using comprehensive global climate models to investigate observed variability and climatology of noctilucent clouds. In this study it is explored to what extent the large-scale inter-annual characteristics of noctilucent clouds are captured in a 30-year run - extending from 1979 to 2009 - of the nudged and extended version of the Canadian Middle Atmosphere Model (CMAM30). To construct and investigate zonal mean inter-seasonal variability in noctilucent cloud occurrence frequency and ice mass density in both hemispheres, a simple cloud model is applied in which it is assumed that the ice content is solely controlled by the local temperature and water vapor volume mixing ratio. The model results are compared to satellite observations, each having an instrument-specific sensitivity when it comes to detecting noctilucent clouds. It is found that the model is able to capture the onset dates of the NLC seasons in both hemispheres as well as the hemispheric differences in NLCs, such as weaker NLCs in the SH than in the NH and differences in cloud height. We conclude that the observed cloud climatology and zonal mean variability are well captured by the model.

Comparison of retrieved noctilucent cloud particle properties from Odin tomography scans and model simulations

Abstract. Mesospheric ice particles, known as noctilucent clouds or polar mesospheric clouds, have long been observed by rocket instruments, satellites and ground-based remote sensing, while models have been used to simulate ice particle growth and cloud properties. However, the fact that different measurement techniques are sensitive to different parts of the ice particle distribution makes it difficult to compare retrieved parameters such as ice particle radius or ice concentration from different experiments. In this work we investigate the accuracy of satellite retrieval based on scattered light and how this affects derived cloud properties. We apply the retrieval algorithm on spectral signals calculated from modelled cloud distributions and compare the results to the properties of the original distributions. We find that ice mass density is accurately retrieved whereas mean radius is often overestimated and high ice concentrations are generally underestimated. The reason is partly that measurements based on scattered light are insensitive to the smaller particles and partly that the retrieval algorithm assumes a Gaussian size distribution. Once we know the limits of the satellite retrieval we proceed to compare the properties retrieved from the modelled cloud distributions to those observed by the Optical, Spectroscopic, and Infrared Remote Imaging System (OSIRIS) instrument on the Odin satellite. We find that a model with a stationary atmosphere, as given by average atmospheric conditions, does not yield cloud properties that are in agreement with the observations, whereas a model with realistic temperature and vertical wind variations does. This indicates that average atmospheric conditions are insufficient to understand the process of noctilucent cloud growth and that a realistic atmospheric variability is crucial for cloud formation and growth. Further, the agreement between results from the model, when set up with a realistically variable atmosphere, and the observations suggests that our understanding of the growth process itself is reasonable.

The relationship between polar mesospheric clouds and their background atmosphere as observed by Odin-SMR and Odin-OSIRIS

Abstract. In this study the properties of polar mesospheric clouds (PMCs) and the background atmosphere in which they exist are studied using measurements from two instruments, OSIRIS and SMR, on board the Odin satellite. The data comes from a set of tomographic measurements conducted by the satellite during 2010 and 2011. The expected ice mass density and cloud frequency for conditions of thermodynamic equilibrium, calculated using the temperature and water vapour as measured by SMR, are compared to the ice mass density and cloud frequency as measured by OSIRIS. We find that assuming thermodynamic equilibrium reproduces the seasonal, latitudinal and vertical variations in ice mass density and cloud frequency, but with a high bias of a factor of 2 in ice mass density. To investigate this bias, we use a simple ice particle growth model to estimate the time it would take for the observed clouds to sublimate completely and the time it takes for these clouds to reform. We find a difference in the median sublimation time (1.8 h) and the reformation time (3.2 h) at peak cloud altitudes (82–84 km). This difference implies that temperature variations on these timescales have a tendency to reduce the ice content of the clouds, possibly explaining the high bias of the equilibrium model. Finally, we detect and are, for the first time, able to positively identify cloud features with horizontal scales of 100 to 300 km extending far below the region of supersaturation ( > 2 km). Using the growth model, we conclude these features cannot be explained by sedimentation alone and suggest that these events may be an indication of strong vertical transport.

Mid-latitude mesospheric clouds and their environment from SOFIE observations

Observations from the Solar Occultation For Ice Experiment (SOFIE) on the Aeronomy of Ice in the Mesosphere (AIM) satellite are used to examine noctilucent clouds (NLC) and their environment at middle latitudes (~56°N and ~52°S). Because SOFIE is uniquely capable of measuring NLC, water vapor, and temperature simultaneously, the local cloud environment can be specified to examine what controls their formation at mid-latitudes. Compared to higher latitudes, mid-latitude NLCs are less frequent and have lower ice mass density, by roughly a factor of five. Compared to higher latitudes at NLC heights, mid-latitude water vapor is only ~12% lower while temperatures are more than 10K higher. As a result the reduced NLC mass and frequency at mid-latitudes can be attributed primarily to temperature. Middle and high latitude NLCs contain a similar amount of meteoric smoke, which was not anticipated because smoke abundance increases towards the equator in summer. SOFIE indicates that mid-latitude NLCs may or may not be associated with supersaturation with respect to ice. It is speculated that this situation is due in part to SOFIE uncertainties related to the limb measurement geometry combined with the non-uniform nature of NLCs. SOFIE is compared with concurrent NLC, temperature, and wind observations from Kühlungsborn, Germany (54°N) during the 2015 summer. The results indicate good agreement in temperature and NLC occurrence frequency, backscatter, and height. SOFIE indicates that NLCs were less frequent over Europe during 2015 compared to other longitudes, in contrast to previous years at higher latitudes that showed no clear longitude dependence. Comparisons of SOFIE and the Solar Backscatter Ultraviolet (SBUV) indicate good agreement in average ice water column (IWC), although differences in occurrence frequency were often large.

Impact of particle shape on the morphology of noctilucent clouds

Abstract. Noctilucent clouds (NLCs) occur during summer in the polar region at altitudes around 83 km. They consist of ice particles with a typical size around 50 nm. The shape of NLC particles is less well known but is important both for interpreting optical measurements and modeling ice cloud characteristics. In this paper, NLC modeling of microphysics and optics is adapted to use cylindrical instead of spherical particle shape. The optical properties of the resulting ice clouds are compared directly to NLC three-color measurements by the Arctic Lidar Observatory for Middle Atmosphere Research (ALOMAR) Rayleigh/Mie/Raman (RMR) lidar between 1998 and 2014. Shape distributions including both needle- and disc-shaped particles are consistent with lidar measurements. The best agreement occurs if disc shapes are 60 % more common than needles, with a mean axis ratio of 2.8. Cylindrical particles cause stronger ice clouds on average than spherical shapes with an increase of backscatter at 532 nm by ≈ 30 % and about 20 % in ice mass density. This difference is less pronounced for bright than for weak ice clouds. Cylindrical shapes also cause NLCs to have larger but a smaller number of ice particles than for spherical shapes.

The influence of PMCs on water vapor and drivers behind PMC variability from SOFIE observations

Observations from the Solar Occultation For Ice Experiment (SOFIE) are used to quantify relationships between polar mesospheric clouds (PMC) and their environment. Dehydration due to ice growth is found to be greatest ∼1.8km above the height of peak ice mass density on average, and H2O enhancement due to sublimation is greatest near the bottom of the PMC layer. The dehydration and hydration layers contain a similar amount of H2O, although less than is found in ice layers, a difference that may be due to meridional transport. Because PMCs modify the surrounding water vapor, PMC–H2O relationships can be misleading and recommendations are made for dealing with this issue. The dependence of PMCs on water vapor and temperature was quantified, accounting for the effects of ice on water vapor. The approach examined inter-annual variations and considered the subset of PMCs detected by the Solar Backscatter Ultraviolet (SBUV) instruments, which are less sensitive than SOFIE. Results in the Northern Hemisphere indicate that PMC variations are dominated by temperature, but that a combination of temperature and water vapor provides the best explanation of the observations. In the Southern Hemisphere PMC variability is attributed primarily to temperature, with water vapor playing a minor role. The subset of SBUV PMCs are found to be one third as sensitive to changing temperature as the entire PMC population observed by SOFIE. Finally, an approach is presented which allows temperature and water vapor anomalies to be estimated from various PMC data sets such as SBUV. Using recently reported SBUV PMC trends at 64–74°N latitude with the results of this study indicates a cooling trend of −0.27±0.14Kdecade−1 and a water vapor increase of +0.66±0.34%decade−1 (both at 80–84km). This cooling trend agrees with reports based on observations in the middle atmosphere at similar latitudes. The water vapor increase is lower than expected due to increasing methane, although this difference may be consistent with H2O loss due to photolysis at PMC altitudes.

Tomographic and spectral views on the lifecycle of polar mesospheric clouds from Odin/OSIRIS

AbstractVertical and horizontal structures of Polar Mesospheric Clouds (PMC) have been recovered by tomographic retrieval from the OSIRIS instrument aboard the Odin satellite. The tomographic algorithm has been used to return local scattering coefficients at seven wavelengths in the ultraviolet. This spectral information is used to retrieve PMC particle sizes, number density, and ice mass density. While substantial horizontal variations are found, local vertical structures are overall consistent with the idea of a growth‐sedimentation process leading to a visible cloud. Large numbers of small particles are present near the top of the observed cloud layer. Toward lower altitudes, particle sizes increase while particle number densities decrease. A close relationship is found between the distribution of local PMC scattering coefficient and ice mass density. The bottom of the cloud often features large particles with mode radii exceeding 70 nm that rain out of the cloud before sublimating. The number density of these large particles is small, and they do not contribute significantly to the overall cloud brightness. As a consequence, the presence of these large particles can be difficult to identify for remote sensing techniques that integrate over the entire cloud column. When it comes to deriving absolute values of particle mode radius and number density, there is a strong sensitivity to assumptions on the mathematical form of the particle size distribution. We see a continued strong need to resolve this issue by co‐analysis of various remote sensing techniques and observation geometries.

Gravitational Gradients at Satellite Altitudes in Global Geophysical Studies

Due to the ESA’s satellite mission GOCE launched in March 2009, gravitational gradients sampled along the orbital trajectory approximately 250 km above the Earth’s surface have become available. Since 2010, gravitational gradients have routinely been applied in geodesy for the derivation of global Earth’s gravitational models provided in terms of fully normalized coefficients in a spherical harmonic series representation of the Earth’s gravitational potential. However, in geophysics, gravitational gradients observed by spaceborne instruments have still been applied relatively seldom. This contribution describes their possible geophysical applications in structural studies where gravitational gradients observed at satellite altitudes are compared with those derived by a spectral forward modeling technique using available global models of selected Earth’s mass components as input data. In particular, GOCE gravitational gradients are interpreted in terms of a superposition principle of gravitation as combined gravitational effects generated by a homogeneous reference ellipsoid of revolution, mean topographic and ice mass density distributions, depth-dependent mass density contrasts within bathymetry and lateral mass density anomalies with sediments and crustal layers. Respective gravitational effects are one by one removed from gravitational gradients observed at approximately 250 km elevation above ground. Removing respective gravitational gradients from observed gravitational gradients gradually reveals problematic geographic areas with model deficiencies. For the full interpretation of observed gravitational gradients, deficiencies of CRUST2.0 must be corrected and effects of deeper laying mass anomalies not included in the study considered. These findings are confirmed by parameters describing spectral properties of the gravitational gradients. The methodology can be applied for validating Earth’s gravitational models and for constraining crustal models in the development phase.

Inter-hemispheric comparison of PMCs and their environment from SOFIE observations

Observations of polar mesospheric clouds (PMC) and their environment from the Solar Occultation For Ice Experiment (SOFIE) are examined to quantify differences between the Northern Hemisphere (NH) and Southern Hemisphere (SH) during summer. The results indicate that hemispheric differences are smaller when using pressure as the vertical coordinate, instead of altitude. The peak in PMC mass density (Zmax) was found to exist 1.2km higher in the SH, but at about the same pressure (∼0.0055hPa) in both hemispheres. This occurs because systematically warmer temperatures in the SH polar summer stratosphere and mesosphere expand the overlying atmosphere to raise the altitudes of pressure levels in the SH mesosphere relative to the NH. For the five southern and five northern PMC seasons observed to date, the primary differences are that PMCs in the Northern Hemisphere are more frequent (24%±32%), have greater ice mass density (65%±26% at Zmax), and exist for a longer seasonal period (10±10 days). These differences are attributed primarily to lower temperatures (4 to 9K) in the north because water vapor differences are small (1.9%±5.4% at Zmax).

The roles of temperature and water vapor at different stages of the polar mesospheric cloud season

Temperature, or alternatively, saturation vapor pressure (PSAT), dominantly controls the polar mesospheric cloud (PMC) seasonal onset and termination, characterized by a strong anticorrelated relationship between the Solar Occultation for Ice Experiment (SOFIE)‐observed PMC frequency and PSAT on intraseasonal time scales. SOFIE is highly sensitive to weak clouds and can obtain a nearly full spectrum of PMCs. Both the SOFIE PMC frequency and PSAT indicate a rapid onset and termination of the season. Compared to PSAT, the water vapor partial pressure (PH2O) exhibits only a slight increase from before to after the start of the season. We are able to use the PSAT daily minimum and two averaged PH2O levels taken before and after the solstice, respectively, to estimate the start and end days of the PMC season within 1–2 days uncertainty. SOFIE ice mass density and its relationship to PH2O and PSAT are examined on intraseasonal scales and for two extreme conditions, i.e., strong and weak cloud cases. In the strong cloud case, such as those bright clouds that occur during the core of the season, PH2O far exceeds PSAT and dominantly controls the ice mass density variation, while in the weak cloud case, such as those clouds that occur at the start and end of the season, PH2O and PSAThave comparable magnitudes, vary in concert, and have similar effects on the ice mass density variation. These results suggest that the long‐term brightness trends reported by DeLand et al. (2007) are primarily driven by changes in water vapor (H2O), not temperature.

Quantitative relation between PMSE and ice mass density

Abstract. Radar reflectivities associated with Polar Mesosphere Summer Echoes (PMSE) are compared with measurements of ice mass density in the mesopause region. The 54.5 MHz radar Moveable Atmospheric Radar for Antarctica (MARA), located at the Wasa/Aboa station in Antarctica (73° S, 13° W) provided PMSE measurements in December 2007 and January 2008. Ice mass density was measured by the Solar Occultation for Ice Experiment (SOFIE). The radar operated continuously during this period but only measurements close to local midnight are used for comparison, to coincide with the local time of the measurements of ice mass density. The radar location is at high geographic latitude but low geomagnetic latitude (61°) and the measurements were made during a period of very low solar activity. As a result, background electron densities can be modelled based on solar illumination alone. We find a close correlation between the time and height variations of radar reflectivity and ice mass density, at all PMSE heights, from 80 km up to 95 km. A quantitative expression relating radar reflectivities to ice mass density is found, including an empirical dependence on background electron density. Using this relation, we can use PMSE reflectivities as a proxy for ice mass density, and estimate the daily variation of ice mass density from the daily variation of PMSE reflectivities. According to this proxy, ice mass density is maximum around 05:00–07:00 LT, with lower values around local noon, in the afternoon and in the evening. This is consistent with the small number of previously published measurements and model predictions of the daily variation of noctilucent (mesospheric) clouds and in contrast to the daily variation of PMSE, which has a broad daytime maximum, extending from 05:00 LT to 15:00 LT, and an evening-midnight minimum.

Relationships between polar mesospheric clouds, temperature, and water vapor from Solar Occultation for Ice Experiment (SOFIE) observations

The goal of this work is to explore relationships between polar mesospheric clouds (PMCs), temperature, and water vapor and to understand the extent that bulk thermodynamic equilibrium can explain observed PMC characteristics. We use observations from the Solar Occultation for Ice Experiment (SOFIE) and employ a simple PMC model which assumes that ice exists in thermodynamic equilibrium with the local temperature and water vapor. Model results using SOFIE temperatures and water vapor are found to reproduce the observed ice layer altitudes, ice frequency versus time and altitude, ice mass density (expressed as the gas phase equivalent contained in the ice phase, Qice) versus time and altitude, and the vertical column abundance of ice (or ice water content (IWC)). The differences (model ‐ SOFIE) for July 2008 were −0.1 km in the altitude of peak ice mass density (Zmax), 16% in Qice at Zmax, and 35% in IWC. These results suggest that on average, PMCs can exist in equilibrium with the surrounding environment, and the results also imply that ice nucleation may occur throughout the PMC altitude range. Good correlations were found between ice abundance and temperature (or saturation ratio), although knowledge of both water vapor and temperature is required for a quantitative prediction of observed ice characteristics. Our results indicate that the seasonal dependence of ice abundance is generally controlled by temperature and that in a broad sense, changes in water vapor are a result of changes in ice. We also find that lower temperatures are associated with higher ice mass density, higher ice concentration, and slightly smaller particle radii. This finding indicates that the increase in ice mass density is due to the nucleation of more particles rather than the growth of existing ice, and this finding points to nucleation as an important factor in determining PMC variability.