The Arctic region is known to be very sensitive to climate change. Clouds and in particular mixed-phase clouds (MPCs) remain one of the greatest sources of uncertainties in the modelling of the ...Arctic response to climate change due to an inaccurate representation of their variability and their quantification. In this study, we present a characterisation of the vertical, spatial and seasonal variability of Arctic clouds and MPCs over the entire Arctic region based on satellite active remote sensing observations. MPC properties in the region of the Svalbard archipelago (78° N, 15° E) are also investigated. The occurrence frequency of clouds and MPCs are determined from CALIPSO/CLOUDSAT measurements processed with the DARDAR retrieval algorithm, which allow for a reliable cloud thermodynamic phase classification (warm liquid, supercooled liquid, ice, mixing of ice and supercooled liquid). Significant differences are observed between MPC properties over the entire Arctic region and over the Svalbard region. Results show that MPCs are encountered all year long, with a minimum occurrence of 30% in winter and 50% during the rest of the year on average over the entire Arctic. Over the Svalbard region, MPC occurrence is more constant with time with larger values (55%) compared to the average observed in the Arctic. MPCs are especially located at low altitudes, below 3000 m, where their frequency of occurrence reaches 90%, particularly during winter, spring and autumn. Moreover, results highlight that MPCs are statistically more frequent above open sea than land or sea ice. The temporal and spatial distribution of MPCs over the Svalbard region seems to be linked to the supply of moister air and warmer water from the North Atlantic Ocean, which contribute to the initiation of the liquid water phase. Over the whole Arctic, and particularly in western regions, the increase of MPC occurrence from spring to autumn could be connected to the sea ice melting. During this period, the open water transports some of the warm water from the North Atlantic Ocean to the rest of the Arctic region. This facilitates the vertical transfer of moisture and thus the persistence of the liquid phase. Particular attention is also paid to the measurement uncertainties and how they could affect our conclusions.
We compare the cloud detection and cloud phase determination of three independent climatologies based on Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) to airborne in ...situ measurements. Our analysis of the cloud detection shows that the differences between the satellite and in situ measurements mainly arise from three factors. First, averaging CALIPSO Level l data along track before cloud detection increases the estimate of high‐ and low‐level cloud fractions. Second, the vertical averaging of Level 1 data before cloud detection tends to artificially increase the cloud vertical extent. Third, the differences in classification of fully attenuated pixels among the CALIPSO climatologies lead to differences in the low‐level Arctic cloud fractions. In another section, we compare the cloudy pixels detected by colocated in situ and satellite observations to study the cloud phase determination. At midlatitudes, retrievals of homogeneous high ice clouds by CALIPSO data sets are very robust (more than 94.6% of agreement with in situ). In the Arctic, where the cloud phase vertical variability is larger within a 480 m pixel, all climatologies show disagreements with the in situ measurements and CALIPSO‐General Circulation Models‐Oriented Cloud Product (GOCCP) report significant undefined‐phase clouds, which likely correspond to mixed‐phase clouds. In all CALIPSO products, the phase determination is dominated by the cloud top phase. Finally, we use global statistics to demonstrate that main differences between the CALIPSO cloud phase products stem from the cloud detection (horizontal averaging, fully attenuated pixels) rather than the cloud phase determination procedures.
Key Points
Comparison of the cloud and cloud phase of three CALIPSO climatologies with in situ measurements
Cloud detection differences due to vertical/horizontal averaging and fully attenuated pixels
Very high agreement for midlatitude ice clouds, more disagreement with the mixed‐phase clouds
There is growing evidence that marine microorganisms may influence cloud cover over the ocean through their impact on sea spray and trace gas emissions, further forming cloud droplets or ice ...crystals. However, evidence of a robust causal relationship based on observations is still pending. In this study, we use 4 years of multi‐instrument satellite data to segregate low‐level clouds into ice‐containing and liquid‐water clouds to obtain clear relationships between cloud types and ocean biological tracers, especially with nanophytoplankton cell abundances. Results suggest that microorganisms may be involved in compensating effects on cloud properties, increasing the frequency of occurrence of warm‐liquid clouds, and decreasing the occurrence of ice‐containing clouds in most regions during springtime. The relationships observed in most regions do not apply to the South Pacific Ocean in the 40°S–50°S latitude band. These results shed light on overlooked potential compensating effects of ocean microorganisms on cloud cover.
Plain Language Summary
Climate is governed by interactions between the ocean and the atmosphere. While physical interactions such as exchanges of heat and water vapor are fairly well understood, the role of biology, that is, the living marine microorganisms, on atmospheric processes, is a lot more complex. For instance, marine microorganisms may influence the number and the chemical composition of sea sprays and also emit trace gasses that will form tiny particles. Sea sprays and newly formed particles can then serve as nuclei on which cloud droplets or ice crystals form, therefore influencing cloud properties and climate. These chains of processes are theoretical, and there are few clear linkages between ocean biology and cloud properties derived from observational data. This study uses new satellite retrievals to establish relationships between cloud phase occurrence (ice, warm‐liquid, mixed‐phase or supercooled‐liquid clouds) and the biological activity of the ocean in different regions of the southern ocean. For a given month, locations of higher abundance of phytoplankton corresponds to a higher warm‐liquid cloud cover but lower ice cloud cover. These results suggest compensating effects of marine microorganisms on cloud lifetime via their potential to impact the formation of particles able to become water droplets or ice crystals.
Key Points
Nanophytoplankton biomass shows more relations to cloud occurrences than Chlorophyll‐a or Particulate Organic Carbon concentrations
Higher nanophytoplankon abundance is positively linked to warm‐liquid cloud frequency of occurrence in spring in most regions of 40°S–60°S
Higher nanophytoplankton abundance is linked to a decrease in the ice‐containing cloud frequency of occurrence in most regions
Snow consists of non-spherical grains of various shapes and sizes. Still, in many radiative transfer applications, single-scattering properties of snow have been based on the assumption of spherical ...grains. More recently, second-generation Koch fractals have been employed. While they produce a relatively flat phase function typical of deformed non-spherical particles, this is still a rather ad hoc choice. Here, angular scattering measurements for blowing snow conducted during the CLimate IMpacts of Short-Lived pollutants In the Polar region (CLIMSLIP) campaign at Ny Ålesund, Svalbard, are used to construct a reference phase function for snow. Based on this phase function, an optimized habit combination (OHC) consisting of severely rough (SR) droxtals, aggregates of SR plates and strongly distorted Koch fractals is selected. The single-scattering properties of snow are then computed for the OHC as a function of wavelength λ and snow grain volume-to-projected area equivalent radius rvp. Parameterization equations are developed for λ = 0.199–2.7 μm and rvp = 10–2000 μm, which express the single-scattering co-albedo β, the asymmetry parameter g and the phase function P11 as functions of the size parameter and the real and imaginary parts of the refractive index. The parameterizations are analytic and simple to use in radiative transfer models. Compared to the reference values computed for the OHC, the accuracy of the parameterization is very high for β and g. This is also true for the phase function parameterization, except for strongly absorbing cases (β > 0.3). Finally, we consider snow albedo and reflected radiances for the suggested snow optics parameterization, making comparisons to spheres and distorted Koch fractals.
Seasonal physicochemical characteristics of North Atlantic marine aerosols are presented for the period from January 2002 to June 2004. The aerosol size distribution modal diameters show seasonal ...variations, 0.031 μm in winter and 0.049 μm in summer for the Aitken mode and 0.103 μm in winter and 0.177 μm in summer for the accumulation mode. The accumulation mode mass also showed a seasonal variation, minimum in winter and maximum in summer. A supermicron sized particle mode was found at 2 μm for all seasons showing 30% higher mass concentration during winter than summer resulting from higher wind speed conditions. Chemical analysis showed that the concentration of sea salt has a seasonal pattern, minimum in summer and maximum in winter because of a dependency of sea‐salt load on wind speeds. By contrast, the non‐sea‐salt (nss) sulphate concentration in fine mode particles exhibited lower values during winter and higher values during midsummer. The water soluble organic carbon (WSOC) and total carbon (TC) analysis also showed a distinctive seasonal pattern. The WSOC concentration during the high biological activity period peaked at 0.2 μgC m−3, while it was lower than 0.05 μgC m−3 during the low biological activity period. The aerosol light scattering coefficient showed a minimum value of 5.5 Mm−1 in August and a maximum of 21 Mm−1 in February. This seasonal variation was due to the higher contribution of sea salt in the MBL during North Atlantic winter. By contrast, aerosols during late spring and summer exhibited larger angstrom parameters than winter, indicating a large contribution of the biogenically driven fine or accumulation modes. Seasonal characteristics of North Atlantic marine aerosols suggest an important link between marine aerosols and biological activity through primary production of marine aerosols.
•Heterogeneous cirrus clouds are generated.•Lidar signals are simulated using a Monte-Carlo code.•Effects on CALIOP lidar measured data are evaluated.•Importance of horizontal photon transport is ...underscored.
The goal of this work is to evaluate the effects of cirrus heterogeneity on characteristics that are directly measured by the CALIOP/CALIPSO lidar, i.e. attenuated backscatter coefficient and depolarization ratio. This assessment was done using the 3D Monte Carlo simulator of Polarized Lidar signals (3DMcPOLID) together with the high-resolution 3D cloud fields-generator 3DCLOUD_V2. The evaluation is based on random sampling and on comparison between mean profiles of 3D clouds and of plane-parallel equivalent 1D clouds.
Mean profiles of the apparent attenuated backscatter as well as of the integrated apparent backscatter are statistically equal when a cirrus cloud field is probed with the 325 m resolution. To the contrary, the difference between profiles is statistically significant in the case of the 1 km resolution. Profiles of the volume depolarization ratio are statistically different for both cases of the horizontal resolution. The total bias of CALIOP/CALIPSO lidar data is mainly due to the plane parallel bias and multiple scattering, i.e., horizontal photon transport.
Cirrus are cloud types that are recognized to have a strong impact on the Earth-atmosphere radiation balance. This impact is however still poorly understood, due to the difficulties in describing the ...large variability of their properties in global climate models. Consequently, numerous airborne and space-borne missions have been dedicated to their study in the last decades. The satellite constellation A-Train has for instance proven to be particularly helpful for the study of cirrus. More particularly, the Infrared Imaging Radiometer (IIR) carried onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite shows a great sensitivity to the radiative and microphysical properties of these clouds. Our study presents a novel methodology that uses the thermal infrared measurements of IIR to retrieve the ice crystal effective size and optical thickness of cirrus. This methodology is based on an optimal estimation scheme, which possesses the advantage of attributing precise uncertainties to the retrieved parameters. Two IIR airborne validation campaigns have been chosen as case studies for illustrating the results of our retrieval method. It is observed that optical thicknesses could be accurately retrieved but that large uncertainties may occur on the effective diameters. Strong agreements have also been found between the products of our method when separately applied to the measurements of IIR and of the airborne radiometer CLIMAT-AV, which consolidates the results of previous validation studies of IIR level-1 measurements. Comparisons with in situ observations and with operational products of IIR are also discussed and appear to be coherent with our results. However, we have found that the quality of our retrievals can be strongly impacted by uncertainties related to the choice of a pristine crystal model and by poor constraints on the properties of possible liquid cloud layers underneath cirrus. Simultaneous retrievals of liquid clouds radiative and microphysical properties and/or the use of different ice crystal models should therefore be considered in order to improve the quality of the results.
The aim of this paper is to present the Monte Carlo code McRALI that
provides simulations under multiple-scattering regimes of polarized high-spectral-resolution (HSR) lidar and Doppler radar ...observations for
a three-dimensional (3D) cloudy atmosphere. The effects of nonuniform beam
filling (NUBF) on HSR lidar and Doppler radar signals related to the
EarthCARE mission are investigated with the help of an academic 3D
box cloud characterized by a single isolated jump in cloud optical depth,
assuming vertically constant wind velocity. Regarding Doppler radar signals,
it is confirmed that NUBF induces a severe bias in velocity estimates. The
correlation of the NUBF bias of Doppler velocity with the horizontal
gradient of reflectivity shows a correlation coefficient value around 0.15 m s−1 (dBZ km-1)-1, close to that given in the scientific
literature. Regarding HSR lidar signals, we confirm that multiple-scattering
processes are not negligible. We show that NUBF effects on molecular,
particulate, and total attenuated backscatter are mainly due to unresolved
variability of cloud inside the receiver field of view and, to a lesser
extent, to the horizontal photon transport. This finding gives some insight
into the reliability of lidar signal modeling using independent column
approximation (ICA).
Clouds have an important role in Earth's radiative budget. Since the late 1970s, considerable instrumental developments have been made in order to quantify cloud microphysical and optical properties, ...for both airborne and ground-based applications. Intercomparison studies have been carried out in the past to assess the reliability of cloud microphysical properties inferred from various measurement techniques. However, observational uncertainties still exist, especially for droplet size distribution measurements and need to be reduced. In this work, we discuss results from an intercomparison campaign, performed at the Puy de Dôme in May 2013. During this campaign, a unique set of cloud instruments was operating simultaneously in ambient air conditions and in a wind tunnel. A Particle Volume Monitor (PVM-100), a Forward Scattering Spectrometer Probe (FSSP), a Fog Monitor (FM-100), and a Present Weather Detector (PWD) were sampling on the roof of the station. Within a wind tunnel located underneath the roof, two Cloud Droplet Probes (CDPs) and a modified FSSP (SPP-100) were operating. The main objectives of this paper are (1) to study the effects of wind direction and speed on ground-based cloud observations, (2) to quantify the cloud parameters discrepancies observed by the different instruments, and (3) to develop methods to improve the quantification of the measurements. The results revealed that all instruments showed a good agreement in their sizing abilities, both in terms of amplitude and variability. However, some of them, especially the FM-100, the FSSP and the SPP, displayed large discrepancies in their capability to assess the magnitude of the total number concentration of the cloud droplets. As a result, the total liquid water content can differ by up to a factor of 5 between the probes. The use of a standardization procedure, based on data of integrating probes (PVM-100 or visibilimeter) and extinction coefficient comparison substantially enhanced the instrumental agreement. During this experiment, the total concentration agreed in variations with the visibilimeter, except for the FSSP, so a corrective factor can be applied and it ranges from 0.44 to 2.2. This intercomparison study highlights the necessity to have an instrument which provides a bulk measurement of cloud microphysical or optical properties during cloud ground-based campaigns. Moreover, the FM and FSSP orientation was modified with an angle ranging from 30 to 90° angle with wind speeds from 3 to 7 m s−1. The results show that the induced number concentration loss is between 29 and 98 % for the FSSP and between 15 and 68 % for the FM-100. In particular, FSSP experiments showed strong discrepancies when the wind speed was lower than 3 m s−1 and/or when the angle between the wind direction and the orientation of the instruments is greater than 30°. An inadequate orientation of the FSSP towards the wind direction leads to an underestimation of the measured effective diameter.
The 3DCLOUD algorithm for generating stochastic three-dimensional (3-D) cloud fields is described in this paper. The generated outputs are 3-D optical depth (τ) for stratocumulus and cumulus fields ...and 3-D ice water content (IWC) for cirrus clouds. This model is designed to generate cloud fields that share some statistical properties observed in real clouds such as the inhomogeneity parameter ρ (standard deviation normalized by the mean of the studied quantity), the Fourier spectral slope β close to −5/3 between the smallest scale of the simulation to the outer Lout (where the spectrum becomes flat). Firstly, 3DCLOUD assimilates meteorological profiles (humidity, pressure, temperature and wind velocity). The cloud coverage C, defined by the user, can also be assimilated, but only for stratocumulus and cumulus regime. 3DCLOUD solves drastically simplified basic atmospheric equations, in order to simulate 3-D cloud structures of liquid or ice water content. Secondly, the Fourier filtering method is used to constrain the intensity of ρ, β, Lout and the mean of τ or IWC of these 3-D cloud structures. The 3DCLOUD model was developed to run on a personal computer under Matlab environment with the Matlab statistics toolbox. It is used to study 3-D interactions between cloudy atmosphere and radiation.
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