scholarly journals Toward autonomous surface-based infrared remote sensing of polar clouds: retrievals of cloud optical and microphysical properties

2019 ◽  
Vol 12 (9) ◽  
pp. 5071-5086 ◽  
Author(s):  
Penny M. Rowe ◽  
Christopher J. Cox ◽  
Steven Neshyba ◽  
Von P. Walden
Keyword(s):  
Climate Model ◽  
Effective Radius ◽  
The Arctic ◽  
Polar Regions ◽  
Cloud Property ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Instrument Resolution ◽  
Mean Square Errors ◽  
Ice Fraction

Abstract. Improvements to climate model results in polar regions require improved knowledge of cloud properties. Surface-based infrared (IR) radiance spectrometers have been used to retrieve cloud properties in polar regions, but measurements are sparse. Reductions in cost and power requirements to allow more widespread measurements could be aided by reducing instrument resolution. Here we explore the effects of errors and instrument resolution on cloud property retrievals from downwelling IR radiances for resolutions of 0.1 to 20 cm−1. Retrievals are tested on 336 radiance simulations characteristic of the Arctic, including mixed-phase, vertically inhomogeneous, and liquid-topped clouds and a variety of ice habits. Retrieval accuracy is found to be unaffected by resolution from 0.1 to 4 cm−1, after which it decreases slightly. When cloud heights are retrieved, errors in retrieved cloud optical depth (COD) and ice fraction are considerably smaller for clouds with bases below 2 km than for higher clouds. For example, at a resolution of 4 cm−1, with errors imposed (noise and radiation bias of 0.2 mW/(m2 sr cm−1) and biases in temperature of 0.2 K and in water vapor of −3 %), using retrieved cloud heights, root-mean-square errors decrease from 1.1 to 0.15 for COD, 0.3 to 0.18 for ice fraction (fice), and 10 to 7 µm for ice effective radius (errors remain at 2 µm for liquid effective radius). These results indicate that a moderately low-resolution, surface-based IR spectrometer could provide cloud property retrievals with accuracy comparable to existing higher-resolution instruments and that such an instrument would be particularly useful for low-level clouds.

scholarly journals Toward autonomous surface-based infrared remote sensing of polar clouds: Retrievals of cloud microphysical properties

2019 ◽  
Author(s):  
Penny M. Rowe ◽  
Christopher J. Cox ◽  
Steven Neshyba ◽  
Von P. Walden
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Effective Radius ◽  
Mixed Phase ◽  
The Arctic ◽  
Polar Regions ◽  
Microphysical Properties ◽  
Instrument Resolution ◽  
Retrieval Errors ◽  
Measurement Biases

Abstract. Improvements to climate model results in polar regions require improved knowledge of cloud microphysical properties. Surface-based infrared radiance spectrometers have been used to retrieve cloud microphysical properties in polar regions, but measurements are sparse. Reductions in cost and power requirements to allow more widespread measurements could be aided by reducing instrument resolution. Here we explore the effect of errors and instrument resolution on cloud microphysical property retrievals from downwelling infrared radiances for resolutions of 0.1 to 8 cm−1. Retrievals are tested on 331 radiance simulations characteristic of the Arctic, including mixed-phase, vertically inhomogeneous, and liquid-topped clouds and a variety of ice habits. Results indicate that measurement biases lead to biases in retrieved properties that are not represented by the retrieval error covariance matrix. Retrieval errors are high if mixed-phase is assumed throughout liquid-topped ice clouds. Errors due to assuming ice habit is spherical are progressively larger for solid columns, plates, and hollow bullet rosettes. Using retrieved cloud heights, particularly when errors are imposed, increases retrieval errors but decreases sensitivity to incorrect ice habits and vertical variation. Results indicate that retrieval accuracy is unaffected by resolution from 0.1 to 2 cm−1, after which it decreases only slightly. At a resolution of 4 cm−1, for typical errors expected in temperature (0.2 K) and water vapour (3 %), and assuming radiation bias and noise of 0.2 mW/(m2 sr cm−1), using retrieved cloud heights, error estimates are 0.1 ± 0.6 for optical depth, 0.0 ± 0.3 for ice fraction, 0 &plusmnl 2 μm for effective radius of liquid, and 2 ± 2 μm for effective radius of ice. These results indicate that a moderately low resolution, portable, surface-based infrared spectrometer could provide microphysical properties to help constrain climate models.

scholarly journals FAME-C: cloud property retrieval using synergistic AATSR and MERIS observations

2014 ◽  
Vol 7 (11) ◽  
pp. 3873-3890 ◽  
Author(s):  
C. K. Carbajal Henken ◽  
R. Lindstrot ◽  
R. Preusker ◽  
J. Fischer
Keyword(s):  
Optical Thickness ◽  
Single Layer ◽  
Cloud Water ◽  
Effective Radius ◽  
Cloud Property ◽  
Microphysical Properties ◽  
Microphysical Property ◽  
Resolution Imaging ◽  
Cloud Optical Thickness ◽  
Cloud Water Path

Abstract. A newly developed daytime cloud property retrieval algorithm, FAME-C (Freie Universität Berlin AATSR MERIS Cloud), is presented. Synergistic observations from the Advanced Along-Track Scanning Radiometer (AATSR) and the Medium Resolution Imaging Spectrometer (MERIS), both mounted on the polar-orbiting Environmental Satellite (Envisat), are used for cloud screening. For cloudy pixels two main steps are carried out in a sequential form. First, a cloud optical and microphysical property retrieval is performed using an AATSR near-infrared and visible channel. Cloud phase, cloud optical thickness, and effective radius are retrieved, and subsequently cloud water path is computed. Second, two cloud top height products are retrieved based on independent techniques. For cloud top temperature, measurements in the AATSR infrared channels are used, while for cloud top pressure, measurements in the MERIS oxygen-A absorption channel are used. Results from the cloud optical and microphysical property retrieval serve as input for the two cloud top height retrievals. Introduced here are the AATSR and MERIS forward models and auxiliary data needed in FAME-C. Also, the optimal estimation method, which provides uncertainty estimates of the retrieved property on a pixel basis, is presented. Within the frame of the European Space Agency (ESA) Climate Change Initiative (CCI) project, the first global cloud property retrievals have been conducted for the years 2007–2009. For this time period, verification efforts are presented, comparing, for four selected regions around the globe, FAME-C cloud optical and microphysical properties to cloud optical and microphysical properties derived from measurements of the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra satellite. The results show a reasonable agreement between the cloud optical and microphysical property retrievals. Biases are generally smallest for marine stratocumulus clouds: −0.28, 0.41 μm and −0.18 g m−2 for cloud optical thickness, effective radius and cloud water path, respectively. This is also true for the root-mean-square deviation. Furthermore, both cloud top height products are compared to cloud top heights derived from ground-based cloud radars located at several Atmospheric Radiation Measurement (ARM) sites. FAME-C mostly shows an underestimation of cloud top heights when compared to radar observations. The lowest bias of −0.3 km is found for AATSR cloud top heights for single-layer clouds, while the highest bias of −3.0 km is found for AATSR cloud top heights for multilayer clouds. Variability is low for MERIS cloud top heights for low-level clouds, and high for MERIS cloud top heights for mid-level and high-level single-layer clouds, as well as for both AATSR and MERIS cloud top heights for multilayer clouds.

scholarly journals The variability of tropical ice cloud properties as a function of the large-scale context from ground-based radar-lidar observations over Darwin, Australia

2011 ◽  
Vol 11 (16) ◽  
pp. 8363-8384 ◽  
Author(s):  
A. Protat ◽  
J. Delanoë ◽  
P. T. May ◽  
J. Haynes ◽  
C. Jakob ◽  
...  
Keyword(s):  
Large Scale ◽  
Effective Radius ◽  
Ice Clouds ◽  
Ice Cloud ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Ice Water Content ◽  
Mean Differences ◽  
Ice Water ◽  
Lidar Observations

Abstract. The high complexity of cloud parameterizations now held in models puts more pressure on observational studies to provide useful means to evaluate them. One approach to the problem put forth in the modelling community is to evaluate under what atmospheric conditions the parameterizations fail to simulate the cloud properties and under what conditions they do a good job. It is the ambition of this paper to characterize the variability of the statistical properties of tropical ice clouds in different tropical "regimes" recently identified in the literature to aid the development of better process-oriented parameterizations in models. For this purpose, the statistical properties of non-precipitating tropical ice clouds over Darwin, Australia are characterized using ground-based radar-lidar observations from the Atmospheric Radiation Measurement (ARM) Program. The ice cloud properties analysed are the frequency of ice cloud occurrence, the morphological properties (cloud top height and thickness), and the microphysical and radiative properties (ice water content, visible extinction, effective radius, and total concentration). The variability of these tropical ice cloud properties is then studied as a function of the large-scale cloud regimes derived from the International Satellite Cloud Climatology Project (ISCCP), the amplitude and phase of the Madden-Julian Oscillation (MJO), and the large-scale atmospheric regime as derived from a long-term record of radiosonde observations over Darwin. The vertical variability of ice cloud occurrence and microphysical properties is largest in all regimes (1.5 order of magnitude for ice water content and extinction, a factor 3 in effective radius, and three orders of magnitude in concentration, typically). 98 % of ice clouds in our dataset are characterized by either a small cloud fraction (smaller than 0.3) or a very large cloud fraction (larger than 0.9). In the ice part of the troposphere three distinct layers characterized by different statistically-dominant microphysical processes are identified. The variability of the ice cloud properties as a function of the large-scale atmospheric regime, cloud regime, and MJO phase is large, producing mean differences of up to a factor 8 in the frequency of ice cloud occurrence between large-scale atmospheric regimes and mean differences of a factor 2 typically in all microphysical properties. Finally, the diurnal cycle of the frequency of occurrence of ice clouds is also very different between regimes and MJO phases, with diurnal amplitudes of the vertically-integrated frequency of ice cloud occurrence ranging from as low as 0.2 (weak diurnal amplitude) to values in excess of 2.0 (very large diurnal amplitude). Modellers should now use these results to check if their model cloud parameterizations are capable of translating a given atmospheric forcing into the correct statistical ice cloud properties.

scholarly journals Cloud vertical distribution from combined surface and space radar–lidar observations at two Arctic atmospheric observatories

2017 ◽  
Vol 17 (9) ◽  
pp. 5973-5989 ◽  
Author(s):  
Yinghui Liu ◽  
Matthew D. Shupe ◽  
Zhien Wang ◽  
Gerald Mace
Keyword(s):  
Vertical Distribution ◽  
Climate Models ◽  
Cloud Fraction ◽  
The Arctic ◽  
Active Sensors ◽  
Annual Cycles ◽  
Cloud Property ◽  
Microphysical Properties ◽  
Cloud Water Content ◽  
Vertical Distributions

Abstract. Detailed and accurate vertical distributions of cloud properties (such as cloud fraction, cloud phase, and cloud water content) and their changes are essential to accurately calculate the surface radiative flux and to depict the mean climate state. Surface and space-based active sensors including radar and lidar are ideal to provide this information because of their superior capability to detect clouds and retrieve cloud microphysical properties. In this study, we compare the annual cycles of cloud property vertical distributions from space-based active sensors and surface-based active sensors at two Arctic atmospheric observatories, Barrow and Eureka. Based on the comparisons, we identify the sensors' respective strengths and limitations, and develop a blended cloud property vertical distribution by combining both sets of observations. Results show that surface-based observations offer a more complete cloud property vertical distribution from the surface up to 11 km above mean sea level (a.m.s.l.) with limitations in the middle and high altitudes; the annual mean total cloud fraction from space-based observations shows 25–40 % fewer clouds below 0.5 km than from surface-based observations, and space-based observations also show much fewer ice clouds and mixed-phase clouds, and slightly more liquid clouds, from the surface to 1 km. In general, space-based observations show comparable cloud fractions between 1 and 2 km a.m.s.l., and larger cloud fractions above 2 km a.m.s.l. than from surface-based observations. A blended product combines the strengths of both products to provide a more reliable annual cycle of cloud property vertical distributions from the surface to 11 km a.m.s.l. This information can be valuable for deriving an accurate surface radiative budget in the Arctic and for cloud parameterization evaluation in weather and climate models. Cloud annual cycles show similar evolutions in total cloud fraction and ice cloud fraction, and lower liquid-containing cloud fraction at Eureka than at Barrow; the differences can be attributed to the generally colder and drier conditions at Eureka relative to Barrow.

scholarly journals AMALi – the Airborne Mobile Aerosol Lidar for Arctic research

2010 ◽  
Vol 10 (6) ◽  
pp. 2947-2963 ◽  
Author(s):  
I. S. Stachlewska ◽  
R. Neuber ◽  
A. Lampert ◽  
C. Ritter ◽  
G. Wehrle
Keyword(s):  
Weather Conditions ◽  
The Arctic ◽  
Unknown Boundary ◽  
Polar Regions ◽  
Raman Lidar ◽  
Reliable Operation ◽  
Marine Research ◽  
Cloud Properties ◽  
Iterative Inversion ◽  
532 Nm

Abstract. The Airborne Mobile Aerosol Lidar (AMALi) is an instrument developed at the Alfred Wegener Institute for Polar and Marine Research for reliable operation under the challenging weather conditions at the Earth's polar regions. Since 2003 the AMALi has been successfully deployed for measurements in ground-based installation and zenith- or nadir-pointing airborne configurations during several scientific campaigns in the Arctic. The lidar provides backscatter profiles at two wavelengths (355/532 nm or 1064/532 nm) together with the linear depolarization at 532 nm, from which aerosol and cloud properties can be derived. This paper presents the characteristics and capabilities of the AMALi system and gives examples of its usage for airborne and ground-based operations in the Arctic. As this backscatter lidar normally does not operate in aerosol-free layers special evaluation schemes are discussed, the nadir-pointing iterative inversion for the case of an unknown boundary condition and the two-stream approach for the extinction profile calculation if a second lidar system probes the same air mass. Also an intercomparison of the AMALi system with an established ground-based Koldewey Aerosol Raman Lidar (KARL) is given.

scholarly journals The Changing Energy Balance of the Polar Regions in a Warmer Climate

2013 ◽  
Vol 26 (10) ◽  
pp. 3112-3129 ◽  
Author(s):  
Lennart Bengtsson ◽  
Kevin I. Hodges ◽  
Symeon Koumoutsaris ◽  
Matthias Zahn ◽  
Paul Berrisford
Keyword(s):  
Polar Region ◽  
Energy Transport ◽  
Climate Model ◽  
Radiant Energy ◽  
Surface Radiation ◽  
The Arctic ◽  
Polar Regions ◽  
Energy Fluxes ◽  
Intergovernmental Panel ◽  
Static Energy

Abstract Energy fluxes for polar regions are examined for two 30-yr periods, representing the end of the twentieth and twenty-first centuries, using data from high-resolution simulations with the ECHAM5 climate model. The net radiation to space for the present climate agrees well with data from the Clouds and the Earth’s Radiant Energy System (CERES) over the northern polar region but shows an underestimation in planetary albedo for the southern polar region. This suggests there are systematic errors in the atmospheric circulation or in the net surface energy fluxes in the southern polar region. The simulation of the future climate is based on the Intergovernmental Panel on Climate Change (IPCC) A1B scenario. The total energy transport is broadly the same for the two 30-yr periods, but there is an increase in the moist energy transport on the order of 6 W m−2 and a corresponding reduction in the dry static energy. For the southern polar region the proportion of moist energy transport is larger and the dry static energy correspondingly smaller for both periods. The results suggest a possible mechanism for the warming of the Arctic that is discussed. Changes between the twentieth and twenty-first centuries in the northern polar region show the net ocean surface radiation flux in summer increases ~18 W m−2 (24%). For the southern polar region the response is different as there is a decrease in surface solar radiation. It is suggested that this is caused by changes in cloudiness associated with the poleward migration of the storm tracks.

scholarly journals Comparison of CALIPSO-Like, LaRC, and MODIS Retrievals of Ice-Cloud Properties over SIRTA in France and Florida during CRYSTAL-FACE

2007 ◽  
Vol 46 (3) ◽  
pp. 249-272 ◽  
Author(s):  
M. Chiriaco ◽  
H. Chepfer ◽  
P. Minnis ◽  
M. Haeffelin ◽  
S. Platnick ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Radiant Energy ◽  
Energy System ◽  
Effective Radius ◽  
Cloud Detection ◽  
Regional Study ◽  
Crystal Face ◽  
Ice Clouds ◽  
Microphysical Properties ◽  
Cloud Properties

Abstract This study compares cirrus-cloud properties and, in particular, particle effective radius retrieved by a Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO)-like method with two similar methods using Moderate-Resolution Imaging Spectroradiometer (MODIS), MODIS Airborne Simulator (MAS), and Geostationary Operational Environmental Satellite imagery. The CALIPSO-like method uses lidar measurements coupled with the split-window technique that uses the infrared spectral information contained at the 8.65-, 11.15-, and 12.05-μm bands to infer the microphysical properties of cirrus clouds. The two other methods, using passive remote sensing at visible and infrared wavelengths, are the operational MODIS cloud products (using 20 spectral bands from visible to infrared, referred to by its archival product identifier MOD06 for MODIS Terra) and MODIS retrievals performed by the Clouds and the Earth’s Radiant Energy System (CERES) team at Langley Research Center (LaRC) in support of CERES algorithms (using 0.65-, 3.75-, 10.8-, and 12.05-μm bands); the two algorithms will be referred to as the MOD06 and LaRC methods, respectively. The three techniques are compared at two different latitudes. The midlatitude ice-clouds study uses 16 days of observations at the Palaiseau ground-based site in France [Site Instrumental de Recherche par Télédétection Atmosphérique (SIRTA)], including a ground-based 532-nm lidar and the MODIS overpasses on the Terra platform. The tropical ice-clouds study uses 14 different flight legs of observations collected in Florida during the intensive field experiment known as the Cirrus Regional Study of Tropical Anvils and Cirrus Layers–Florida Area Cirrus Experiment (CRYSTAL-FACE), including the airborne cloud-physics lidar and the MAS. The comparison of the three methods gives consistent results for the particle effective radius and the optical thickness but discrepancies in cloud detection and altitudes. The study confirms the value of an active remote sensing method (CALIPSO like) for the study of subvisible ice clouds, in both the midlatitudes and Tropics. Nevertheless, this method is not reliable in optically very thick tropical ice clouds, because of their particular microphysical properties.

scholarly journals AMALi – the Airborne Mobile Aerosol Lidar for Arctic research

2009 ◽  
Vol 9 (5) ◽  
pp. 18745-18792 ◽  
Author(s):  
I. S. Stachlewska ◽  
R. Neuber ◽  
A. Lampert ◽  
C. Ritter ◽  
G. Wehrle
Keyword(s):  
Present State ◽  
Aerosol Particles ◽  
Weather Conditions ◽  
The Arctic ◽  
Polar Regions ◽  
Marine Research ◽  
The Past ◽  
Cloud Properties ◽  
And Performance

Abstract. The Airborne Mobile Aerosol Lidar (AMALi) is an instrument developed at the Alfred Wegener Institute for Polar and Marine Research for a trouble-free operation under the challenging weather conditions at the Earth's polar regions. Since 2003 the AMALi has been successfully deployed for measurements in the ground-based installation and the zenith- or nadir-aiming airborne configurations during several scientific campaigns in the Arctic. The lidar provides profiles of the total backscatter at two wavelengths, from which aerosol and cloud properties are derived. It measures also the linear depolarization of the backscattered return, allowing for the discrimination of thermodynamic cloud phase and the identification of the presence of non-spherical aerosol particles. This paper presents the capability characteristics and performance of the past and present state of the AMALi system, as well as discusses the ground-based and airborne evaluation schemes applied to invert the data.

scholarly journals Development and evaluation of surface shortwave flux parameterizations for use in sea-ice models

1997 ◽  
Vol 25 ◽  
pp. 33-37
Author(s):  
Jeffrey R. Key ◽  
Yong Liu ◽  
Robert S. Stone
Keyword(s):  
Sea Ice ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
The Arctic ◽  
Polar Regions ◽  
Computationally Efficient ◽  
Using Data ◽  
One Year ◽  
Mean Square Errors

The surface radiation budget of the polar regions strongly influences ice growth and melt. Thermodynamic sea-ice models therefore require accurate yet computationally efficient methods of computing radiative fluxes. In this paper a new parameterization of the downwelling shortwave radiation flux at the Arctic surface is developed and compared to a variety of existing schemes. Parameterized llnxes are compared to in situ measurements using data for one year at Barrow, Alaska. Our results show that the new parameterization can estimate the downwelling shortwave flux with mean and root mean square errors of 1 and 5%, respectively, for clear conditions and 5 and 20% for cloudy conditions. The new parameterization offers a unified approach to estimating downwelling shortwave fluxes under clear and cloudy conditions, and is more accurate than existing schemes.

scholarly journals Polar Cooling Effect Due to Increase of Phytoplankton and Dimethyl-Sulfide Emission

Atmosphere ◽  
2018 ◽  
Vol 9 (10) ◽  
pp. 384 ◽  
Author(s):  
Ah-Hyun Kim ◽  
Seong Yum ◽  
Hannah Lee ◽  
Dong Chang ◽  
Sungbo Shim
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Climate Models ◽  
Dimethyl Sulfide ◽  
Climate Model ◽  
Cloud Condensation Nuclei ◽  
Marine Phytoplankton ◽  
The Arctic ◽  
Polar Regions ◽  
Cloud Albedo

The effects of increased dimethyl-sulfide (DMS) emissions due to increased marine phytoplankton activity are examined using an atmosphere-ocean coupled climate model. As the DMS emission flux from the ocean increases globally, large-scale cooling occurs due to the DMS-cloud condensation nuclei (CCN)-cloud albedo interactions. This cooling increases as DMS emissions are further increased, with the most pronounced effect occurring over the Arctic, which is likely associated with a change in sea-ice fraction as sea ice mediates the air-sea exchange of the radiation, moisture and heat flux. These results differ from recent studies that only considered the bio-physical feedback that led to amplified Arctic warming under greenhouse warming conditions. Therefore, climate negative feedback from DMS-CCN-cloud albedo interactions that involve marine phytoplankton and its impact on polar climate should be properly reflected in future climate models to better estimate climate change, especially over the polar regions.

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