Thick Clouds Research Articles

Estimating Phase Transition Rates in Shallow Cumulus Clouds from Mass Flux. Part II: Vertically dependent formulation

Abstract This work continued the investigation of the relationship between phase transition rates and mass flux in trade wind cumulus clouds. The latter were simulated by an LES model initialized with soundings from the RICO field project. In Part I (Kogan, 2022) we demonstrated that a very high correlation exists between integral phase transition rates and upward mass flux. In this study we focused on the vertically dependent variables and showed that a similar high correlation exists between the condensation rate 𝒞 (z) and the upward mass flux ℳ (z). Based on condensation theory, we showed that under quasi-steady approximation condensation rates can be calculated by a linear function of ℳ with the slope coefficient dependent only on temperature and pressure. The model data showed that the error of such approximation is less than a few tenths of a percent. The parameterization of the evaporation process is more complex, mostly because of the slow evaporation of raindrops as they fall through the cloud’s unsaturated areas. Nevertheless, it was possible to define the fraction of evaporation to condensation rate as a function of vertical coordinate z and cloud thickness H. This function can be quite accurately approximated by the 3rd order polynomials of z and H. It is suggested that proposed formulation of evaporation together with the quasi-steady formulation of condensation can serve as a parameterization of water phase transition rates in shallow cumulus clouds.

Analysis of Macro- and Microphysical Characteristics of Ice Clouds over the Tibetan Plateau Using CloudSat/CALIPSO Data

Utilizing CloudSat/CALIPSO satellite data and ERA5 reanalysis data from 2007 to 2016, this study analyzed the distributions of optical and physical characteristics and change characteristics of ice clouds over the Tibetan Plateau (TP). The results show that the frequency of ice clouds in the cold season (November to March) on the plateau is over 80%, while in the warm season (May to September) it is around 60%. The average cloud base height of ice clouds in the warm season is 3–5 km, and mostly around 2 km in the cold season. The average cloud top height in the warm season is around 5–8 km, while in the cold season it is mainly around 4.5 km. The average thickness of ice clouds in both seasons is around 2 km. The statistical results of microphysical characteristics show that the ice water content is around 10−1 to 103 mg/m3, and the effective radius of ice clouds is mainly in the range of 10–90 μm. Both have their highest frequency in the west of the TP and lowest in the northeast. A comprehensive analysis of the change in temperature, water vapor, and ice cloud occurrence frequency shows that the rate of increase in water vapor in the warm season is greater than that in the cold season, while the rates of increase in both surface temperature and ice cloud occurrence are smaller than in the cold season. The rate of increase in temperature in the warm season is around 0.038 °C/yr, and that in the cold season is around 0.095 °C/yr. The growth rate of thin ice clouds in the warm season is around 0.15% per year, while that in the cold season is as high as 1% per year. The results suggest that the surface temperature change may be related to the occurrence frequency of thin ice clouds, with the notable increase in temperature during the cold season possibly being associated with a significant increase in the occurrence frequency of thin ice clouds.

Cirrus cloud occurrence and its geometrical and optical properties during the transient monsoon conditions

Knowledge of variation in the percentage occurrence of the cirrus clouds (POC) during transient monsoon conditions is essential for understanding the role of the monsoon in transporting the water vapor into the lower stratosphere which is vital in quantifying the radiation budget of the earth–atmosphere system. In this paper, we present the spatial structure of the POC, the geometrical properties such as cloud top and base height (CTH & CBH), cloud thickness (CTH-CBH), optical properties such as optically thick, thin, and subvisible cirrus clouds during the active and break phases of the Asian summer monsoon using Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) during July–August 2006–2018. The active and break phases are identified based on the central India rainfall from the India Meteorological Department dataset. The POC is found to be higher by 10–30 % over central India and some parts of the eastern Arabian Sea (AS) and Bay of Bengal (BoB) during the active phase compared to the break phase which shows enhancement in POC over the foothill of Himalaya and southern part of BoB and AS. The higher POC is attributed to the increase in the convective activities associated with the increase in tropical easterly jet during the active phase. The CTH and CBH range ~14–18 km and 12–16 km, respectively during the active phase compared to the break phase. The contributions of optically thick and thin clouds are higher in POC during both phases compared to subvisible clouds. Both convectively generated and in situ-formed cirrus clouds dominate during the active phase compared to the break phase indicating the dominance of the freeze-drying processes during the active phase.

Removing thick clouds in landsat 8 OLI images with cloudy time-series auxiliary data

Abstract Thick cloud occlusion severely limits the subsequent application of optical remote-sensing images. Existing mainstream cloud removal methods often use cloud-free homologous temporal images to provide auxiliary information. However, due to the limitation of cloud occlusion and satellite revisit cycle, the time interval between the cloud-free auxiliary image and the target cloudy image is often too large, and the possible land cover changes during the period increase the uncertainty of effective information on the auxiliary images. In this case, more accurate reconstructions may be obtained by using temporally closer and partially cloud-contaminated images. In this paper, a deep network, convLSTM, is developed for cloud removal (i.e., CR-convLSTM), which makes full use of the complementary effective information on partially cloud-contaminated time-series images. Experiments based on simulated clouds indicated that CR-convLSTM can obtain more accurate predictions than the classical cloud removal method MNSPI. CR-convLSTM is an effective cloud removal method with high computational efficiency while ensuring predicting accuracy.

Use of satellite data to determine the cloud optical depths present during overirradiance conditions

Abstract Overirradiance conditions can negatively impact the operation of photovoltaic systems if no protective measures have been implemented, leading to potential damages and economic losses in photovoltaic generation plants. Current simulation models attempt to understand the mechanism of overirradiance conditions. However, their observations still differ significantly from experimental ones, emphasizing the need to better understand the two main hypotheses that account for overirradiance events: reflection at the edges of thick clouds and Mie scattering in thin clouds. This paper studies the qualitative correlation between the global tilted irradiance measured by a spectroradiometer on the surface and the optical depth of the clouds measured by the GOES-16 satellite to shed more light on this phenomenon. Our results show a good qualitative correlation between the global tilted irradiance and the optical depth of the clouds present during overirradiance events. We also show that all overirradiance conditions occurred when thick clouds were present. These results indicate that the overirradiance events analyzed have been produced predominantly by reflections at the edges of thick clouds, supporting the hypothesis that the increase in global irradiance is mainly due to a substantial increase in direct irradiance.

Balmer Decrement Anomalies in Galaxies at z ∼ 6 Found by JWST Observations: Density-bounded Nebulae or Excited H i Clouds?

We investigate the physical origins of the Balmer decrement anomalies in GS-NDG-9422 and RXCJ2248-ID galaxies at z ∼ 6 whose Hα/Hβ values are significantly smaller than 2.7, the latter of which also shows anomalous Hγ/Hβ and Hδ/Hβ values beyond the errors. Because the anomalous Balmer decrements are not reproduced under the Case B recombination, we explore the nebulae with optical depths smaller and larger than the Case B recombination by physical modeling. We find two cases quantitatively explaining the anomalies: (1) density-bounded nebulae that are opaque only up to around Lyγ–Ly8 transitions and (2) ionization-bounded nebulae partly/fully surrounded by optically thick excited H i clouds. The case of (1) produces more Hβ photons via Lyγ absorption in the nebulae, requiring fine tuning in optical depth values, while this case helps ionizing photon escape for cosmic reionization. The case of (2) needs the optically thick excited Hi clouds with N 2 ≃ 1012−1013 cm−2, where N 2 is the column density of the hydrogen atom with the principal quantum number of n = 2. Interestingly, the high N 2 values qualitatively agree with the recent claims for GS-NDG-9422 with the strong nebular continuum requiring a number of 2s-state electrons and for RXCJ2248-ID with the dense ionized regions likely coexisting with the optically thick clouds. While the physical origin of the optically thick excited H i clouds is unclear, these results may suggest gas clouds with excessive collisional excitation caused by an amount of accretion and supernovae in the high-z galaxies.

Nightside Clouds on Tidally Locked Terrestrial Planets Mimic Atmosphere-free Scenarios

We investigate the impact of nightside cloud formation on the observable day/night contrast of tidally locked terrestrial planet atmospheres. We demonstrate that, in the case where the planetary dayside is only 10 s of Kelvin hotter than the planetary nightside, the presence of optically thick nightside clouds can lead to observations that mimic a planet without an atmosphere, despite the planet actually hosting a significant (10 bar) atmosphere. The scenario presented in this work requires a level of intrinsic atmospheric day/night temperature contrast such that the nightside can form clouds while the dayside is too hot for cloud formation to occur. This scenario is most likely for hotter terrestrials and terrestrials with low volatile inventories. We thus note that a substantial dayside/nightside temperature difference alone does not robustly indicate that a planet does not host an atmosphere, and additional observations and modeling are essential for characterization. We further discuss several avenues for future study to improve our understanding of the terrestrial planets and how best to characterize them with JWST.

Planetary Waves Drive Horizontal Variations in Trace Species in the Venus Deep Atmosphere

Abstract The deep atmosphere of Venus remains mysterious because of the planet’s high, optically thick cloud decks. While phenomena such as the observed decadal fluctuations in sulfur dioxide abundance above the clouds could shed light on conditions below, poor understanding of vertical and horizontal transport limits such an approach. Nightside spectral windows permit observation of trace gas species in the lower atmosphere, but incomplete understanding of the circulation makes the distribution of these species challenging to interpret. We performed two simulations with the Venus Planetary Climate Model including an age of air calculation to investigate tracer transport (a) between the surface and the stagnant lower haze layer and (b) between the cloud deck and the observable upper atmosphere. We find a timescale on the order of many decades for surface-to-lower haze layer transport and ∼1.4 yr from the lowest cloud deck to 101 km. The extreme slowness of transport from the surface to the clouds makes it unlikely that compositional variability at the surface could affect the upper atmosphere sulfur dioxide abundance on observed timescales. Planetary-scale Rossby waves with a zonal wavenumber of 1 in both hemispheres are found to circumnavigate the planet in the deep atmosphere in 36 Earth days. These waves are associated with gyres that collect tracers and areas of upwelling that transport them to higher altitudes, leading to significantly younger air at polar latitudes in the altitude range of 25–45 km. The existence of chemically enhanced traveling Rossby gyres could explain the observed deep atmosphere carbon monoxide variability.

Robustness of the relationship between tropical high-cloud cover and large-scale circulations

High clouds play an important role in climate variations by shading the sun and contributing to the greenhouse effect. It has been suggested that these variations are strongly controlled by atmospheric circulations; however, the relationship between high clouds and circulations in global simulations has been confirmed only for a limited number of general circulation models (GCMs). Increasing our understanding of this relationship requires a more complete dataset of state-of-the-art GCMs. This study quantifies the relationship between high clouds and circulations by spatial and temporal correlation using data from 28 atmospheric GCMs along with a global nonhydrostatic model, a new-type of GCM, and reveals a robust and strong relationship in most models. This study also finds that the sensitivity, which is defined as the slope of the relationship between high clouds and mass fluxes of circulations, is highly model-dependent. This suggests that a similar change of circulations does not guarantee that of high clouds, which could be one reason for the complexity in projecting high-cloud changes due to warming. Moreover, this study confirms in both observation and models that the relationship with circulations is stronger for medium-thickness and thick high clouds than for thin clouds. Furthermore, the relationship between high clouds and circulations is more convincing in near-equatorial regions between 15°S–15°N, the ascending branch of the Hadley circulation, where deep convection is especially active.

Relationship between vertical variation of cloud microphysical properties and thickness of the entrainment interfacial layer in Physics of Stratocumulus Top stratocumulus clouds

AbstractThis study examines the vertical variations of cloud microphysics and their correlation with the thickness of the entrainment interfacial layer (EIL) in stratocumulus clouds, observed in the Physics of Stratocumulus Top (POST) aircraft measurement campaign. From the mixing fraction analysis, we identified EIL between the free atmosphere and cloud top for all 15 POST flights, and found that EIL thickness significantly influenced the vertical variation of cloud microphysics and thermodynamics. In several flights, a trend toward stronger homogeneous mixing traits with increasing depth from the cloud top was found, indicative of the vertical movement of mixed (i.e., entrainment‐affected and diluted) parcels. However, in one flight, this trend was limited to the middle part of the cloud only, with the correlation between virtual potential temperature and liquid water content being strongly negative near the cloud top, suggesting limited downward movement of mixed parcels. Another important finding is that there was a robust negative correlation between long‐wave cooling rate near the cloud top and EIL thickness, highlighting differences in radiative cooling rates between mixed and unmixed parcels due to differences in liquid water content between them. These insightful findings will be crucial for enhancing our understanding of the role of EIL in modulating entrainment and the vertical movement of mixed parcels in stratocumulus clouds.

Efficient On-Board Compression for Arbitrary-Shaped Cloud-Covered Remote Sensing Images via Adaptive Filling and Controllable Quantization

Due to the fact that invalid cloud-covered regions in remote sensing images consume a considerable quantity of coding bit rates under the limited satellite-to-ground transmission rate, existing image compression methods suffer from low compression efficiency and poor reconstruction quality, especially in cloud-free regions which are generally regarded as regions of interest (ROIs). Therefore, we propose an efficient on-board compression method for remote sensing images with arbitrary-shaped clouds by leveraging the characteristics of cloudy images. Firstly, we introduce two novel spatial preprocessing strategies, namely, the optimized adaptive filling (OAF) strategy and the controllable quantization (CQ) strategy. Specifically, the OAF strategy fills each cloudy region using the contextual information at its inner and outer edge to completely remove the information of cloudy regions and minimize their coding consumption, which is suitable for images with only thick clouds. The CQ strategy implicitly identifies thin and thick clouds and rationally quantifies the data in cloudy regions to alleviate information loss in thin cloud-covered regions, which can achieve the balance between coding efficiency and reconstructed image quality and is more suitable for images containing thin clouds. Secondly, we develop an efficient coding method for a binary cloud mask to effectively save the bit rate of the side information. Our method provides the flexibility for users to choose the desired preprocessing strategy as needed and can be embedded into existing compression framework such as JPEG2000. Experimental results on the GF-1 dataset show that our method effectively reduces the coding consumption of invalid cloud-covered regions and significantly improve the compression efficiency as well as the quality of decoded images.

Improving Atmospheric Temperature and Relative Humidity Profiles Retrieval Based on Ground-Based Multichannel Microwave Radiometer and Millimeter-Wave Cloud Radar

Obtaining temperature and humidity profiles with high vertical resolution is essential for describing and predicting atmospheric motion, and, in particular, for understanding the evolution of medium- and small-scale weather processes, making short-range and near-term weather forecasting, and implementing weather modifications (artificial rainfall, artificial rain elimination, etc.). Ground-based microwave radiometers can acquire vertical tropospheric atmospheric data with high temporal and spatial resolution. However, the accuracy of temperature and relative humidity retrieval is still not as accurate as that of radiosonde data, especially in cloudy conditions. Therefore, improving the observation and retrieval accuracy is a major challenge in current research. The focus of this study was to further improve the accuracy of atmospheric temperature and humidity profile retrieval and investigate the specific effects of cloud information (cloud-base height and cloud thickness) on temperature and humidity profile retrieval. The observation data from the ground-based multichannel microwave radiometer (GMR) and the millimeter-wave cloud radar (MWCR) were incorporated into the retrieval process of the atmospheric temperature and relative humidity profiles. The retrieval was performed using the backpropagation neural network (BPNN). The retrieval results were quantified using the mean absolute error (MAE) and root mean square error (RMSE). The statistical results showed that the temperature profiles were less affected by the cloud information compared with the relative humidity profiles. Cloud thickness was the main factor affecting the retrieval of relative humidity profiles, and the retrieval with cloud information was the best retrieval method. Compared with the retrieval profiles without cloud information, the MAE and RMSE values of most of the altitude layers were reduced to different degrees after adding cloud information, and the relative humidity (RH) errors of some altitude layers were reduced by approximately 50%. The maximum reduction in the RMSE and MAE values for the retrieval of temperature profiles with cloud information was about 1.0 °C around 7.75 km, and the maximum reduction in RMSE and MAE values for the relative humidity profiles was about 10%, which was obtained around 2 km.

Superheated fuel sprays: A comparative study of flash boiling ammonia fuel sprays with methanol, ethanol, and gasoline for multi-hole fuel injection

The rising energy demand creates a huge need to explore and implement sustainable alternative fuels e.g., ammonia, hydrogen, methanol, ethanol, etc. to mitigate emission challenges and significantly lower CO2 emissions. Ammonia has gained much attention as promising alternative fuels for internal combustion engines due to its carbon-neutral nature, which can reduce the carbon footprint in transportation. The advantages of ammonia as a fuel includes carbon-free nature, high volumetric energy density compared to hydrogen, and renewable resource-based production. However, there is lack of the deep understanding of the ammonia spray characteristics and fuel-air mixing process, in particular, the superheated spray, which potentially improve the vaporization and fuel-air mixing. This study focused on investigating the impact of superheating on ammonia, methanol, ethanol, and gasoline fuel sprays by heating the fuel injector tip from non-evaporating to flash boiling temperatures. The fundamental spray parameters were investigated in a constant volume spray chamber using a multihole solenoid driven injector for 150 bar constant injection pressure under 10 bar and 30 bar chamber pressure conditions. To observe flash boiling and the dual-phase flow, a Z-type Schlieren imaging technique, known for its sensitivity to density gradients, was used. The experimental results indicated that ammonia spray behavior significantly differed from other tested fuels for both under cold and superheated conditions. The effect of superheating on methanol, ethanol, and gasoline sprays was very similar, resulting in the shrinkage of spray width and the merging of adjacent plumes into a single thick cloud of spray for elevated tip temperatures. However, ammonia sprays exhibited considerable differences in evaporative conditions, developing a more significant dual phase flow than other fuels upon increment in tip temperature. Overall, the results showed that the spray tip penetration and area for all tested fuels reduced upon heating.

Theoretical and experimental analyses and optimizations of direct coupling photovoltaic-thermoelectric systems

A photovoltaic-thermoelectric (PV-TE) system is modeled theoretically and demonstrated experimentally. Mathematical formulations of the system are proposed according to energy conservation and finite-time thermodynamics, which can be applicable to analyze and optimize the system that consists of commercial photovoltaic (PV) cells and thermoelectric generators (TEGs). The genetic algorithm is introduced to maximize the system's power by optimizing multiple parameters. In Yan'an City, which is located in the northern Shaanxi Province in northwest China, the actual solar irradiance is recorded for almost a full year and the proposed model is verified. Theoretical and experimental results are analyzed and compared. It is found that there are several independent structure parameters in the PV-TE systems and they should be optimized simultaneously to maximize the performance. The PV-TE system's maximum theoretical average power of 0.343 W is 2.69 % greater than the solo PV cell's maximum theoretical power of 0.334 W. The measured average power of the system of 0.317 W is 0.32 % more than that of a solo PV cell of 0.316 W. The duration of strong lighting in Yan'an City reaches 8 h every day for nearly one year and the irradiation intensity can approach 1000 W/m2. The solar radiance is weakly affected by the seasonal changes of four seasons but is greatly affected by rainy days and cloud thickness. The research findings can serve as a helpful guide for the specific implementation of the PV-TE system and exploitation of solar energy resources in northwest China.

Analysis of the Generalization Ability of Defogging Algorithms on RICE Remote Sensing Images.

This paper explores the generalization ability of defogging algorithms on RICE (A Remote Sensing Image Dataset for Cloud Removal) remotely sensed images. RICE is a dataset of remotely sensed images used for removing clouds, allowing the researcher to better evaluate the performance of defogging algorithms for cloud removal from remotely sensed images. In this paper, four classical defogging algorithms, including AOD-Net, FFA-Net, dark channel prior, and DehazeFormer, are selected and applied to the task of de-cloud in RICE remote sensing images. The performance of these algorithms on the RICE dataset is analyzed by comparing the experimental results, and their differences, advantages, and disadvantages in dealing with de-clouded remote sensing images are explored. The experimental results show that the four defogging algorithms are capable of performing well on uniform thin cloud images, but there is a color distortion and the performance is weak when it comes to inhomogeneous clouds as well as thick clouds. So, the generalization ability of the algorithms is weak when the defogging algorithms are applied to the problem of cloud removal. Finally, this paper proposes improvement ideas for the de-cloud problem of RICE remote sensing images and looks forward to possible future research directions.

Large contribution of in-cloud production of secondary organic aerosol from biomass burning emissions

Organic compounds released from wildfires and residential biomass burning play a crucial role in shaping the composition of the atmosphere. The solubility and subsequent reactions of these compounds in the aqueous phase of clouds and fog remain poorly understood. Nevertheless, these compounds have the potential to become an important source of secondary organic aerosol (SOA). In this study, we simulated the aqueous SOA (aqSOA) from residential wood burning emissions under atmospherically relevant conditions of gas-liquid phase partitioning, using a wetted-wall flow reactor (WFR). We analyzed and quantified the specific compounds present in these emissions at a molecular level and determined their solubility in clouds. Our findings reveal that while 1% of organic compounds are fully water-soluble, 19% exhibit moderate solubility and can partition into the aqueous phase in a thick cloud. Furthermore, it is found that the aqSOA generated in our laboratory experiments has a substantial fraction being attributed to the formation of oligomers in the aqueous phase. We also determined an aqSOA yield of 20% from residential wood combustion, which surpasses current estimates based on gas-phase oxidation. These results indicate that in-cloud chemistry of organic gases emitted from wood burning can serve as an efficient pathway to produce organic aerosols, thus potentially influencing climate and air quality.

Improving All‐Sky Simulations of Typhoon Cloud/Rain Band Structures of NOAA‐20 CrIS Window Channel Observations

AbstractThe Cross‐track Infrared Sounder (CrIS) observations (O) contributed greatly to numerical weather prediction. Further contribution depends on the success of all‐sky data assimilation, which requires a method to produce realistic cloud/rain band structures from background fields (i.e., 6‐hr forecasts), and to remove large biases of all‐sky simulation of brightness temperature (TB) in the presence of clouds. In this study, CrIS all‐sky simulations of brightness temperatures at an arbitrarily selected window channel within Typhoon Hinnamnor (2022) are investigated. The 3‐km Weather Research and Forecasting model with three microphysics schemes were used to produce 6‐hr background forecasts (B). The O − B statistic deviate greatly from Gaussian distribution with large biases in either water clouds, or thin ice clouds, or thick ice clouds within Typhoon Hinnamnor. By developing a linear regression function of three all‐sky simulations of TB from 6‐hr forecasts with three microphysics schemes, the O − B statistics approximate a Gaussian normal distribution in water clouds, thin ice clouds and thick ice clouds. Taking the regression function that is established by a training data set to combine 6‐hr background forecasts at later times, the cloud/rain band structures compared much more favorably with CrIS observations than those from an individual microphysic. Furthermore, the regression coefficients derived from Typhoon Hinnamnor (2022) also work for Typhoon Khanun (2023). The work aims to quantify and remove biases in background fields of TB and generating realistic typhoon cloud/rain band structures in background fields will allow a better description of center position, intensity and size to improve typhoon forecasts.

Progressive gap-filling in optical remote sensing imagery through a cascade of temporal and spatial reconstruction models

Filling gaps caused by thick cloud cover or sensor malfunctions has always posed a significant challenge in the preprocessing of optical remote sensing images. The concept of similar pixels, derived from spatial and temporal similarities in remote sensing scenes, has been widely embraced and extensively applied, leading to the development of various gap-filling models. However, in complex scenarios characterized by spatiotemporally heterogeneous surfaces and extensive missing areas, current models often produce noticeable noise-like artifacts, distorted spectral signatures, and unreliable spatial textures. To address this challenge, we propose a simple yet effective similar-pixel-based approach called progressive gap-filling through the cascading temporal and spatial framework (PGFCTS). Drawing inspiration from the negative correlation between spatial distances and the robustness of similar pixels, we employ a progressive gap-filling scheme to ensure that similar pixels are spatially close to the target pixel. This significantly enhances the effectiveness of similar pixels and improves the accuracy of the reconstruction model. Moreover, unlike traditional methods that integrate spatial and temporal information in parallel, our approach integrates these two sources in a cascading manner. Initially, a temporal model is used to obtain preliminary results with fine texture details, followed by a spatial model to enhance spectral fidelity. Through tests on two gap-filling missions and comparisons with seven classical methods, results demonstrate that PGFCTS effectively eliminates noise-like artifacts, faithfully restores spectral features, and accurately reproduces spatial details. Quantitative assessment reveals that PGFCTS consistently outperforms other methods, securing the best scores. Importantly, our method maintains its superiority over extended time intervals between the target and reference images. In summary, PGFCTS emerges as an effective solution for filling missing gaps and reproducing surface information, thereby enhancing the usability of optical images.

The first microwave and submillimetre closure study using particle models of oriented ice hydrometeors to simulate polarimetric measurements of ice clouds

Abstract. The first closure study involving passive microwave and submillimetre measurements of ice clouds with the consideration of oriented particles is presented, using a unique combination of polarised observations from the ISMAR spectral-like radiometer, two radars with frequencies of 35 and 95 GHz, and a variety of in situ instruments. Of particular interest to this study are the large V–H polarised brightness temperature differences measured from ISMAR above a thick frontal ice cloud. Previous studies combining radar and passive submillimetre measurements have not considered polarisation differences. Moreover, they have assumed particle habits a priori. We aim to test whether the large V–H measurements can be simulated successfully by using an atmospheric model consistent with in situ microphysics. An atmospheric model is constructed using information from the in situ measurements, such as the ice water content, the particle size distribution, and the mass and shape of particles, as well as background information obtained from dropsonde profiles. Columnar and dendritic aggregate particle models are generated specifically for this case, and their scattering properties are calculated using the independent monomer approximation under the assumption of horizontal orientation. The scattering properties are used to perform polarised radiative transfer simulations using ARTS to test whether we can successfully simulate the measured large V–H differences. Radar measurements are used to extrapolate the 1-D microphysical profile to derive a time series of particle size distributions which are used to simulate ISMAR brightness temperatures. These simulations are compared to the observations. It is found that particle models that are consistent with in situ microphysics observations are capable of reproducing the brightness temperature depression and polarisation signature measured from ISMAR at the dual-polarised channel of 243 GHz. However, it was required that a proportion of the particles were changed in order to increase the V–H polarised brightness temperature differences. Thus, we incorporated millimetre-sized dendritic crystals, as these particles were observed in the probe imagery. At the second dual-polarised channel of 664 GHz, the brightness temperature depressions were generally simulated at the correct locations; however, the simulated V–H was too large. This work shows that multi-frequency polarisation information could be used to infer realistic particle shapes, orientations, and representations of the split between single crystals and aggregates within the cloud.

On the retrieval of cloud optical thickness from spectral radiances - A sensitivity study with high albedo surfaces

Measurements of spectral zenith radiance in the 320–950 nm wavelength range have been carried out since 2021 at the Thule High Arctic Atmospheric Observatory (THAAO, https://www.thuleatmos-it.it/, 76.5° N, 68.8° W, 225 m a.s.l) located in Pituffik, northern Greenland. This study evaluates whether such observations could provide, in principle, scientifically meaningful cloud optical depth (τ) estimates, what would be the limitations, which are the necessary auxiliary measurements, and which radiance wavelengths would be better suited for the goal. Although clouds play a critical role in the Arctic, a climatology of τ in high albedo conditions is particularly difficult to obtain. THAAO might have the instrument capabilities to provide such a long-term dataset. We use a radiative transfer package to simulate visible spectra with different cloud and surface conditions, assuming homogeneous overcast sky and liquid water clouds of fixed geometrical thickness. Simulations are run to reproduce typical conditions encountered at THAAO when measurements are carried out. We find that the assumption of a broadband albedo instead of a spectrally-resolved one is the source of the largest uncertainties. Tests on size and phase of cloud particles showed that a 50% uncertainty in reff leads to a ∼10% error in τ, and that a 10% contamination of ice crystals in a low-level liquid water cloud leads to an error in τ estimates of less than 5%. All the tests showed that the most critical τ range is between the thin and thick cloud regimes (τ ∼ 7–15), where the retrievals can be less reliable. Otherwise, tests suggest that in the environmental conditions that characterize late spring and summer at THAAO, and given the observatory measurements capabilities, estimates of τ for low-level clouds could be accurately retrieved both in high and low surface albedo conditions by means of zenith radiance measurements in the UV-Vis-NIR range.