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At least 217 records · Page 12

Modeling and parameterization of horizontally inhomogeneous cloud radiative properties

One of the fundamental difficulties in modeling cloud fields is the large variability of cloud optical properties (liquid water content, reflectance, emissivity). The stratocumulus and cirrus clouds, under special consideration for FIRE, exhibit spatial variability on scales of 1 km or less. While it is impractical to model individual cloud elements, the research direction is to model a statistical ensembles of cloud elements with mean-cloud properties specified. The major areas of this investigation are: (1) analysis of cloud field properties; (2) intercomparison of cloud radiative model results with satellite observations; (3) radiative parameterization of cloud fields; and (4) development of improved cloud classification algorithms.

Welch, R. M.↗

Examining the Impact of Overlying Aerosols on the Retrieval of Cloud Optical Properties from Passive Remote Sensing

Haywood et al. (2004) show that an aerosol layer above a cloud can cause a bias in the retrieved cloud optical thickness and effective radius. Monitoring for this potential bias is difficult because space ]based passive remote sensing cannot unambiguously detect or characterize aerosol above cloud. We show that cloud retrievals from aircraft measurements above cloud and below an overlying aerosol layer are a means to test this bias. The data were collected during the Intercontinental Chemical Transport Experiment (INTEX-A) study based out of Portsmouth, New Hampshire, United States, above extensive, marine stratus cloud banks affected by industrial outflow. Solar Spectral Flux Radiometer (SSFR) irradiance measurements taken along a lower level flight leg above cloud and below aerosol were unaffected by the overlying aerosol. Along upper level flight legs, the irradiance reflected from cloud top was transmitted through an aerosol layer. We compare SSFR cloud retrievals from below ]aerosol legs to satellite retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) in order to detect an aerosol ]induced bias. In regions of small variation in cloud properties, we find that SSFR and MODIS-retrieved cloud optical thickness compares within the uncertainty range for each instrument while SSFR effective radius tend to be smaller than MODIS values (by 1-2 microns) and at the low end of MODIS uncertainty estimates. In regions of large variation in cloud properties, differences in SSFR and MODIS ]retrieved cloud optical thickness and effective radius can reach values of 10 and 10 microns, respectively. We include aerosols in forward modeling to test the sensitivity of SSFR cloud retrievals to overlying aerosol layers. We find an overlying absorbing aerosol layer biases SSFR cloud retrievals to smaller effective radii and optical thickness while nonabsorbing aerosols had no impact.

Coddington, O. M.↗

Marine and continental stratocumulus cloud microphysical properties obtained from routine ARM Cimel sunphotometer observations

This study investigates marine and continental stratocumulus (Sc) cloud properties obtained from an automated implementation of a multispectral photometer retrieval. Photometer methods simultaneously retrieve cloud optical depth (τ) and cloud droplet effective radius (r e ), with estimates for liquid water path (LWP) calculated on the availability of those quantities. These applied methods evaluate retrieved cloud properties for Sc identified during a recent 6 year period over the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) program sites in Oklahoma, USA (SGP) and in the Azores, Portugal (ENA). Modest agreement in key quantity retrievals is found between the routine photometer products and multisensor collocated profiling references. Cumulative breakdowns contingent on cloud thickness indicate increases in all retrieved quantities in thicker clouds, with larger discrepancies in the relative performance between the retrievals collected in the presence of drizzle. Under continental cloud conditions, the clouds of a similar thickness and r e to those sampled under marine conditions report a factor of 1.5 larger τ and LWP. An r 2 ≅0.65 is found between photometer τ retrievals and shadowband radiometer measurements, with photometer retrievals reporting a high (relative) bias. The τ intercomparisons indicate that variability between retrievals is a factor of three larger than errors reported from individual retrieval input perturbation tests. Photometer r e retrievals suggest a low r 2 (< 0.1) having a standard deviation ≅ 3 µm when compared to ARM baseline multi-sensor radar/radiometer references (accounting for offsets in the cloud droplet number concentration assumptions of the latter). However, photometer LWP calculations remain relatively unbiased in non-drizzling conditions, with errors O (50 g m −2 ) and r 2 ≅0.5 to collocated radiometer and interferometer references. Additional sensitivity tests for island influences on marine Sc properties suggest that while island-influenced winds may promote larger cloud LWP or thickness, the influence could be within retrieval method uncertainty and/or collocated instrument variability.

54 ENVIRONMENTAL SCIENCES↗

ENSO Tropical Cloud and TOA radiative signatures from the CERES observation

The Clouds and the Earth's Radiant Energy System (CERES) project now has over 15 years accurately observed top-of-the-atmosphere (TOA) flux record for climate monitoring and diagnostic studies. The CERES flux-by-cloud-type dataset, which contains cloud properties and radiative fluxes for 42 cloud types sorted by cloud top pressure and cloud optical depth, is used to investigate the clouds and their associated TOA (top-of-the-atmosphere) fluxes changes over the tropical area during ENSO events during the observed period. Unlike past studies, this study shows the impact of ENSO on cloud properties like optical depth, cloud top effective pressure and temperature and TOA LW and SW fluxes for each sub cloud type. The study reveals the detailed contributions from different cloud types for radiative characteristics during different phases of ENSO. This is especially important for very small net TOA radiative balance due to the cancellation of the fluxes from different cloud types. To further demonstrate the usefulness of this dataset, NCAR Community Atmosphere Model (CAM) is used to simulate the cloud and radiative changes during the period. The model cloud properties are converted to MODIS like cloud properties using modified MODIS simulator. The dataset serves as a more stringent validation of the model for cloud properties and radiative fluxes.

Moguo Sun↗

Tropical and Arctic Cloud Observations From CALIPSO Between 2008-2014 and its Implications

There has been studies (e.g., Schweiger, 2004) suggest significant increase of Arctic clouds during the last three decades, especially in the western Arctic region. Such studies are based on passive remote sensing that are not highly reliable due to the lack of contrasts in temperature and reflectance between clouds and snow/ice surfaces. Changes in the Arctic clouds can be evaluated more accurately using the space-based lidar measurements from CALIPSO during the last nine years since CALIPSO can provide much more accurate detection and classification of both water and ice clouds in the Arctic. Time series of Arctic cloud properties (e.g., cloud fraction, cloud thermodynamic phase, water cloud depolarization ratio and droplet number concentration) from CALIPSO data are analyzed in this study. This study reveals the changes in both cloud fraction and cloud microphysical properties during the last nine years when CALIPSO data are available. We will evaluate the changes in Arctic cloud fraction and cloud microphysical properties, their seasonal and spatial characteristics and the potential impact on the energy budget and the climate of the Arctic.

Hu, Yongxiang↗

The NASA MODIS-VIIRS Continuity Cloud Optical Properties Products

The NASA Aqua MODIS and Suomi National Polar-Orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) climate data record continuity cloud properties products (CLDPROP) were publicly released in April 2019 with an update later that year (Version 1.1). These cloud products, having heritage with the NASA Moderate-resolution Imaging Spectroradiometer (MODIS) MOD06 cloud optical properties product and the NOAA GOES-R Algorithm Working Group (AWG) Cloud Height Algorithm (ACHA), represent an effort to bridge the multispectral imager records of NASA’s Earth Observing System (EOS) and NOAA’s current generation of operational weather satellites to achieve a continuous, multi-decadal climate data record for clouds that can extend well into the 2030s. CLDPROP offers a “continuity of approach,” applying common algorithms and ancillary datasets to both MODIS and VIIRS, including utilizing only a subset of spectral channels available on both sensors to help mitigate instrument differences. The initial release of the CLDPROP_MODIS and CLDPROP_VIIRS data records spans the SNPP observational record (2012-present). Here, we present an overview of the algorithms and an evaluation of the intersensor continuity of the core CLDPROP_MODIS and CLDPROP_VIIRS cloud optical property datasets, i.e., cloud thermodynamic phase, optical thickness, effective particle size, and derived water path. The evaluation includes analyses of pixel-level MODIS/VIIRS co-locations as well as spatial and temporal aggregated statistics, with a focus on identifying and understanding the root causes of individual dataset discontinuities. The results of this evaluation will inform future updates to the CLDPROP products and help scientific users determine the appropriate use of the product datasets for their specific needs.

satellite remote sensing↗

Statistics of Cloud Optical Properties from Airborne Lidar Measurements

Cloud optical properties, such as extinction-to-backscatter ratio and depolarization ratio, have a significant impact on the accuracy of cloud extinction retrievals from lidar systems because parameterizations of these variables are often used in non-ideal conditions to determine cloud type and optical depth. Statistics and trends of these optical parameters were analyzed for four years, 2003-2007, of Cloud Physics Lidar data during five projects of varying geographic locations. Extinction-to-backscatter ratio (at 532 nm) was derived by calculating the transmission loss through the cloud layer, while depolarization ratio was computed using the parallel and perpendicular polarized 1064 nm channels. The majority of the cloud layers yielded an S-ratio between 10 and 40 sr with the S-ratio frequency distribution centered at 25 sr for ice clouds, 21 sr for mixed phase clouds, and 11 sr for water clouds. On average for ice clouds, S ratio slightly decreased with decreasing temperature, while depolarization ratio increased significantly as temperatures decreased. Trends for water and mixed phase clouds were also observed. Ultimately, these observed trends in optical properties as a function of temperature and geographic location will improve current parameterizations of extinction-to-backscatter ratio, which consequently increases accuracy in cloud optical depth and radiative forcing estimates.

Yorks, John E.↗

Collapse models for dark interstellar clouds

Properties of self-consistent numerical hydrodynamic models are compared with observed properties of several dark clouds. The results are consistent with the view that these clouds are undergoing gravitational collapse. The clouds appear to have evolved from similar initial states and to have ages comparable to their free-fall times. Derived cloud masses range between 10 and 1000 solar masses, correlating with cloud size. The models reproduce observed cloud-to-cloud variations in the (C-13)O abundance, and they offer additional evidence that the (C-13)O abundance varies within individual clouds.

Villere, K. R.↗

A system for recording physical properties of clouds

Characterization of the physical properties of clouds is an important objective of the FIRE Project intensive field operations (IFO) planned for 1990 thru 1992. Physical properties observed from satellites will be directly compared to ground based observations during this period. The technical information is provided which is required to record local cloud parameters such as type of clouds, direction of travel, layering, and cloud fraction data. Such information should be very useful in analyzing other cloud and meteorological data. A system of the type described was deployed as part of the First Global Surface Radiation Budget Experiment in April 1989.

Purgold, G. C.↗

Global Weather States and Their Properties from Passive and Active Satellite Cloud Retrievals

In this study, the authors apply a clustering algorithm to International Satellite Cloud Climatology Project (ISCCP) cloud optical thickness-cloud top pressure histograms in order to derive weather states (WSs) for the global domain. The cloud property distribution within each WS is examined and the geographical variability of each WS is mapped. Once the global WSs are derived, a combination of CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) vertical cloud structure retrievals is used to derive the vertical distribution of the cloud field within each WS. Finally, the dynamic environment and the radiative signature of the WSs are derived and their variability is examined. The cluster analysis produces a comprehensive description of global atmospheric conditions through the derivation of 11 WSs, each representing a distinct cloud structure characterized by the horizontal distribution of cloud optical depth and cloud top pressure. Matching those distinct WSs with cloud vertical profiles derived from CloudSat and CALIPSO retrievals shows that the ISCCP WSs exhibit unique distributions of vertical layering that correspond well to the horizontal structure of cloud properties. Matching the derived WSs with vertical velocity measurements shows a normal progression in dynamic regime when moving from the most convective to the least convective WS. Time trend analysis of the WSs shows a sharp increase of the fair-weather WS in the 1990s and a flattening of that increase in the 2000s. The fact that the fair-weather WS is the one with the lowest cloud radiative cooling capability implies that this behavior has contributed excess radiative warming to the global radiative budget during the 1990s.

histograms↗

TPSAS-NF1676L-32084-DND

We present aerosol and cloud observations obtained from the satellite-, aircraft- and ship-based measurements of the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). The data span three seasons (November 2015, May 2016, and September 2017), which correspond to substantial variation in ocean ecosystem characteristics, continental long-range transport, and local aerosol-cloud microphysics and meteorology. For example, below-cloud aerosol number concentrations in November 2015 were of order 10-50 cm-3, while concentrations observed in May and September were of order 100-500 cm-3. Here, we focus on 20 cloud sampling flight modules carried out during NAAMES, which encompass approximately 27 flight hours of the more than 220 NAAMES project flight hours. The nominal cloud module pattern consists of a series of 5-6 vertically-stacked, horizontal flight legs of 10-15 minute duration (~50-90 km in length) that profile the near-surface (300 ft. altitude) and below-cloud aerosol characteristics, the cloud properties near cloud base and top, the aerosol properties above cloud, and finally a high-altitude remote sensing leg that characterizes the cloud top and above-cloud atmosphere. Ship-based aerosol and ceilometer measurements provide the below-cloud context over time, while GOES satellite imagery and cloud retrieval products fill in the above-cloud story.

Richard H Moore↗

Cloud layer thicknesses from a combination of surface and upper-air observations

Cloud layer thicknesses are derived from base and top altitudes by combining 14 years (1975-1988) of surface and upper-air observations at 63 sites in the Northern Hemisphere. Rawinsonde observations are employed to determine the locations of cloud-layer top and base by testing for dewpoint temperature depressions below some threshold value. Surface observations serve as quality checks on the rawinsonde-determined cloud properties and provide cloud amount and cloud-type information. The dataset provides layer-cloud amount, cloud type, high, middle, or low height classes, cloud-top heights, base heights and layer thicknesses, covering a range of latitudes from 0 deg to 80 deg N. All data comes from land sites: 34 are located in continental interiors, 14 are near coasts, and 15 are on islands. The uncertainties in the derived cloud properties are discussed. For clouds classified by low-, mid-, and high-top altitudes, there are strong latitudinal and seasonal variations in the layer thickness only for high clouds. High-cloud layer thickness increases with latitude and exhibits different seasonal variations in different latitude zones: in summer, high-cloud layer thickness is a maximum in the Tropics but a minimum at high latitudes. For clouds classified into three types by base altitude or into six standard morphological types, latitudinal and seasonal variations in layer thickness are very small. The thickness of the clear surface layer decreases with latitude and reaches a summer minimum in the Tropics and summer maximum at higher latitudes over land, but does not vary much over the ocean. Tropical clouds occur in three base-altitude groups and the layer thickness of each group increases linearly with top altitude. Extratropical clouds exhibit two groups, one with layer thickness proportional to their cloud-top altitude and one with small (less than or equal to 1000 m) layer thickness independent of cloud-top altitude.

Poore, Kirk D.↗

The Use of Vegetation For Estimating Broken-Cloud Optical Properties From Surface Measurements

It is known that because of complex three-dimensional (3D) radiative effects of broken clouds, the retrieval of cloud optical properties from upward measurements based on a one-dimensional (1D) inversion technique almost surely fails. To remove radiative effects of 3D cloud structure, we have developed a new technique that retrieves cloud optical thickness for broken clouds above green vegetation from simultaneous surface measurements in the VIS and Near Infrared (NIR) spectral regions. The theoretical basis of the method is the very different spectral behavior of cloud liquid water drops and green vegetation. For example, cloud optical properties, and hence cloud reflectivities, change little between 650 and 860 nm, while the vegetated surface albedo changes from 0.05 to 0.5 between the same two wavelengths. This spectral contrast in surface albedo suggests using ground measurements at both wavelengths not independently, but as an algebraic combination (a spectral index). For a spectral band in the NIR region, the green vegetation acts as a powerful reflector that "illuminates" horizontally inhomogeneous clouds from below. This provides the extra information needed to largely remove the 3D radiative effects, especially in the case of broken clouds; this in turn allows the retrieval of cloud optical depth using traditional 1D radiative transfer theory. This approach is similar to the so-called Green's function problem for radiative transfer where a laser beam illuminates clouds and the resulting "spot-size" of the reflected light around the beam characterizes cloud properties. We generalize Green's function theory to surf ace-cloud interaction and develop new spectral indices from which broken-cloud optical depth can be retrieved.

Marshak, A.↗

Observation of Absorbing Aerosols Above Clouds over the South-East Atlantic Ocean from the Geostationary Satellite SEVIRI – Part 1: Method Description and Sensitivity

High temporal resolution observations from satellites have a great potential for studying the impact of biomass burning aerosols and clouds over the South East Atlantic Ocean (SEAO). This paper presents a method developed to retrieve simultaneously aerosol and cloud properties in aerosol above cloud conditions from the geostationary instrument Meteosat Second Generation/Spinning Enhanced Visible and Infrared Imager (MSG/SEVIRI). The above-cloud Aerosol Optical Thickness (AOT), the Cloud Optical Thickness (COT) and the Cloud droplet Effective Radius (CER) are derived from the spectral contrast and the magnitude of the signal measured in three channels in the visible to shortwave infrared region. The impact of the absorption from atmospheric gases on the satellite signal is corrected by applying transmittances calculated using the water vapour profiles from a Met Office forecast model. The sensitivity analysis shows that a 10% error on the humidity profile leads to an 18.5% bias on the above-cloud AOT, which highlights the importance of an accurate atmospheric correction scheme. In situ measurements from the CLARIFY-2017 airborne field campaign are used to constrain the aerosol size distribution and refractive index that is assumed for the aforementioned retrieval algorithm. The sensitivities in the retrieved AOT, COT and CER to the aerosol model assumptions are assessed. Between 09:00-15:00 UTC, an uncertainty of 40% is estimated on the above-cloud AOT, which is dominated by the sensitivity of the retrieval to the single scattering albedo. The absorption AOT is less sensitive to the aerosol assumptions with an uncertainty generally lower than 17% between 09:00-15:00 UTC. Outside of that time range, as the scattering angle decreases, the sensitivity of the AOT and the absorption AOT to the aerosol model increases. The retrieved cloud properties are only weakly sensitive to the aerosol model assumptions throughout the day, with biases lower than 6% on the COT and 3% on the CER. The stability of the retrieval over time is analysed. For observations outside of the backscattering glory region, the time-series of the aerosol and cloud properties are physically consistent, which confirms the ability of the retrieval to monitor the temporal evolution of aerosol above cloud events over the SEAO.

Peers, Fanny↗

Dependence of Cloud Macrophysical Properties and Phase Distributions on Environmental Conditions Over the North Atlantic and Southern Ocean: Results From COMBLE and MARCUS

The accurate representation of Cold Air Outbreaks (CAOs) and affiliated mixed-phase boundary layer (BL) clouds in models is challenging. How BL cloud properties evolve during CAOs and their dependence on meteorological conditions is not well understood but is important for the simulation of Earth's energy budgets. Here the properties of polar BL clouds over the North Atlantic (NA) and Southern Ocean (SO) are compared using observations from the Measurements of Aerosol Radiation and CloUds over the SO (MARCUS) and CAOs in the Marine BL Experiment (COMBLE) conducted over the NA. MARCUS observations show a stronger BL inversion than COMBLE, with a higher mean EIS (estimated inversion strength)/LTS (lower tropospheric stability) of -0.03 K/13 K compared to COMBLE’s -3.2 K/9.3 K. 39% of CAOs observed during COMBLE were intense with M > 5 K, while MARCUS only had 1.3%. 78%/72% of clouds sampled in CAOs during COMBLE/MARCUS had cloud top heights <4 km. The mean BL cloud top height was over 400 m higher, and the BL was over 500 m deeper for M of 10 K compared to 0 K for both regions. MARCUS observed a 27% moister BL structure than COMBLE when M > 5 K due to stronger BL inversion trapping more moisture within the BL. Under the same LTS, EIS, and M conditions, MARCUS observed a 12% drier BL structure, and clouds were 46% more turbulent than COMBLE. During CAOs, 54% of single-layer BL clouds sampled during MARCUS had liquid-dominated bases compared to 39% during COMBLE.

54 ENVIRONMENTAL SCIENCES↗

Observation of absorbing aerosols above clouds over the south-east Atlantic Ocean from the geostationary satellite SEVIRI – Part 1: Method description and sensitivity

High-temporal-resolution observations from satellites have a great potential for studying the impact of biomass burning aerosols and clouds over the south-east Atlantic Ocean (SEAO). This paper presents a method developed to simultaneously retrieve aerosol and cloud properties in aerosol above-cloud conditions from the geostationary instrument Meteosat Second Generation/Spinning Enhanced Visible and Infrared Imager (MSG/SEVIRI). The above-cloud aerosol optical thickness (AOT), the cloud optical thickness (COT) and the cloud droplet effective radius (CER) are derived from the spectral contrast and the magnitude of the signal measured in three channels in the visible to shortwave infrared region. The impact of the absorption from atmospheric gases on the satellite signal is corrected by applying transmittances calculated using the water vapour profiles from a Met Office forecast model. The sensitivity analysis shows that a 10 % error on the humidity profile leads to an 18.5 % bias on the above-cloud AOT, which highlights the importance of an accurate atmospheric correction scheme. In situ measurements from the CLARIFY-2017 airborne field campaign are used to constrain the aerosol size distribution and refractive index that is assumed for the aforementioned retrieval algorithm. The sensitivities in the retrieved AOT, COT and CER to the aerosol model assumptions are assessed. Between 09:00 and 15:00 UTC, an uncertainty of 40 % is estimated on the above-cloud AOT, which is dominated by the sensitivity of the retrieval to the single-scattering albedo. The absorption AOT is less sensitive to the aerosol assumptions with an uncertainty generally lower than 17 % between 09:00 and 15:00 UTC. Outside of that time range, as the scattering angle decreases, the sensitivity of the AOT and the absorption AOT to the aerosol model increases. The retrieved cloud properties are only weakly sensitive to the aerosol model assumptions throughout the day, with biases lower than 6 % on the COT and 3 % on the CER. The stability of the retrieval over time is analysed. For observations outside of the backscattering glory region, the time series of the aerosol and cloud properties are physically consistent, which confirms the ability of the retrieval to monitor the temporal evolution of aerosol above-cloud events over the SEAO.

cloud properties↗

Ice Cloud Formation and Dehydration in the Tropical Tropopause Layer

Stratospheric water vapor is important not only for its greenhouse forcing, but also because it plays a significant role in stratospheric chemistry. Several recent studies have focused on the potential for dehydration due to ice cloud formation in air rising slowly through the tropical tropopause layer (TTL). Holton and Gettelman showed that temperature variations associated with horizontal transport of air in the TTL can drive ice cloud formation and dehydration, and Gettelman et al. recently examined the cloud formation and dehydration along kinematic trajectories using simple assumptions about the cloud properties. In this study, a Lagrangian, one-dimensional cloud model has been used to further investigate cloud formation and dehydration as air is transported horizontally and vertically through the TTL. Time-height curtains of temperature are extracted from meteorological analyses. The model tracks the growth, advection, and sedimentation of individual cloud particles. The regional distribution of clouds simulated in the model is comparable to the subvisible cirrus distribution indicated by SAGE II. The simulated cloud properties and cloud frequencies depend strongly on the assumed supersaturation threshold for ice nucleation. The clouds typically do not dehydrate the air along trajectories down to the temperature minimum saturation mixing ratio. Rather the water vapor mixing ratio crossing the tropopause along trajectories is 10-50% larger than the saturation mixing ratio. I will also discuss the impacts of Kelvin waves and gravity waves on cloud properties and dehydration efficiency. These simulations can be used to determine whether observed lower stratospheric water vapor mixing ratios can be explained by dehydration associated with in situ TTL cloud formation alone.

Jensen, Eric↗

Effect of CALIPSO Cloud Aerosol Discrimination (CAD) Confidence Levels on Observations of Aerosol Properties near Clouds

CALIPSO aerosol backscatter enhancement in the transition zone between clouds and clear sky areas is revisited with particular attention to effects of data selection based on the confidence level of cloud-aerosol discrimination (CAD). The results show that backscatter behavior in the transition zone strongly depends on the CAD confidence level. Higher confidence level data has a flatter backscatter far away from clouds and a much sharper increase near clouds (within 4 km), thus a smaller transition zone. For high confidence level data it is shown that the overall backscatter enhancement is more pronounced for small clear-air segments and horizontally larger clouds. The results suggest that data selection based on CAD reduces the possible effects of cloud contamination when studying aerosol properties in the vicinity of clouds.

Yang, Weidong↗