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 Cloud vertical distribution from combined surface and space radar/lidar observations at two Arctic atmospheric observations

2017 ◽  
Author(s):  
Yinghui Liu ◽  
Matthew D. Shupe ◽  
Zhien Wang ◽  
Gerald Mace
Keyword(s):  
Vertical Distribution ◽  
Annual Cycle ◽  
Climate Models ◽  
Cloud Fraction ◽  
The Arctic ◽  
Active Sensors ◽  
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 due to their superior capability to detect clouds and retrieve cloud microphysical properties. In this study, we compared the annual cycles of cloud property vertical distributions from satellite active sensors and surface-based active sensors at two Arctic atmospheric observation stations, Barrow and Eureka. We used this data to identify the sensors’ respective strengths and limitations and to develop a blended cloud property vertical distribution by combining both sets of observations. Results show that surface-based observations offer a more detailed cloud property vertical distribution from the surface up to 11 km above mean sea level (AMSL) with limitations in the middle and high altitudes; the annual mean total cloud fraction from space-based observations see 25–40 % fewer clouds below 0.5 km than that from surface-based observations, and space-based observations also show much less ice cloud and mixed phase cloud, and slightly greater liquid cloud from the surface to 1 km; space-based observations show comparable cloud fraction between 1 km and 2 km AMSL, and greater cloud fraction above 2 km AMSL than that from surface-based observations. The blended product combines the strength of both products to provide a more reliable annual cycle of cloud property vertical distribution annual cycle from the surface to 11 km AMSL. 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.

scholarly journals Synergistic radar and sub-millimeter radiometer retrievals of ice hydrometeors in mid-latitude frontal cloud systems

2021 ◽  
Author(s):  
Simon Pfreundschuh ◽  
Stuart Fox ◽  
Patrick Eriksson ◽  
David Duncan ◽  
Stefan A. Buehler ◽  
...  
Keyword(s):  
Climate Models ◽  
Single Scattering ◽  
Gas Absorption ◽  
The Arctic ◽  
Retrieval Algorithm ◽  
Sensor Calibration ◽  
Cloud Systems ◽  
Microphysical Properties ◽  
Ice Particles ◽  
Increased Sensitivity

Abstract. Accurate measurements of ice hydrometeors are required to improve the representation of clouds and precipitation in weather and climate models. In this study, a newly developed, synergistic retrieval algorithm that combines radar with passive millimeter and sub-millimeter observations is applied to observations of three frontally-generated, mid-latitude cloud systems in order to validate the retrieval and asses its capabilities to constrain the properties of ice hydrometeors. To account for uncertainty in the assumed shapes of ice particles, the retrieval is run multiple times while the assumed shape is varied. Good agreement with in situ measurements of ice water content and particle concentrations for particle maximum diameters larger than 200 μm is found for one of the flights for the Large Plate Aggregate and the 6-Bullet Rosette shapes. The variational retrieval fits the observations well although small systematic deviations are observed for some of the sub-millimeter pointing towards issues with the sensor calibration or the modeling of gas absorption. We find that the quality of the fit to the observations is independent of the assumed ice particle shape, indicating that the employed combination of observations is insufficient to constrain the shape of ice particles in the observed clouds. Compared to a radar-only retrieval, the results show an improved sensitivity of the synergistic retrieval to the microphysical properties of ice hydrometeors at the base of the cloud. Our findings indicate that the synergy between active and passive microwave observations improve remote-sensing measurements of ice hydrometeors and may thus help to reduce uncertainties that affect currently available data products. Due to the increased sensitivity to their microphysical properties, the retrieval may also be a valuable tool to study ice hydrometeors in field campaigns. The good fits obtained to the observations increases confidence in the modeling of clouds in the Atmospheric Radiative Transfer Simulator and the corresponding single scattering database, which were used to implement the retrieval forward model. Our results demonstrate the suitability of these tools to produce realistic simulations for upcoming sub-millimeter sensors such as the Ice Cloud Image or the Arctic Weather Satellite.

scholarly journals Influence of the Arctic Oscillation on the vertical distribution of clouds as observed by the A-Train constellation of satellites

2012 ◽  
Vol 12 (21) ◽  
pp. 10535-10544 ◽  
Author(s):  
A. Devasthale ◽  
M. Tjernström ◽  
M. Caian ◽  
M. A. Thomas ◽  
B. H. Kahn ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
Large Scale ◽  
Arctic Oscillation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Dominant Mode ◽  
The Arctic ◽  
Dipole Structure ◽  
The Arctic Oscillation

Abstract. The main purpose of this study is to investigate the influence of the Arctic Oscillation (AO), the dominant mode of natural variability over the northerly high latitudes, on the spatial (horizontal and vertical) distribution of clouds in the Arctic. To that end, we use a suite of sensors onboard NASA's A-Train satellites that provide accurate observations of the distribution of clouds along with information on atmospheric thermodynamics. Data from three independent sensors are used (AQUA-AIRS, CALIOP-CALIPSO and CPR-CloudSat) covering two time periods (winter half years, November through March, of 2002–2011 and 2006–2011, respectively) along with data from the ERA-Interim reanalysis. We show that the zonal vertical distribution of cloud fraction anomalies averaged over 67–82° N to a first approximation follows a dipole structure (referred to as "Greenland cloud dipole anomaly", GCDA), such that during the positive phase of the AO, positive and negative cloud anomalies are observed eastwards and westward of Greenland respectively, while the opposite is true for the negative phase of AO. By investigating the concurrent meteorological conditions (temperature, humidity and winds), we show that differences in the meridional energy and moisture transport during the positive and negative phases of the AO and the associated thermodynamics are responsible for the conditions that are conducive for the formation of this dipole structure. All three satellite sensors broadly observe this large-scale GCDA despite differences in their sensitivities, spatio-temporal and vertical resolutions, and the available lengths of data records, indicating the robustness of the results. The present study also provides a compelling case to carry out process-based evaluation of global and regional climate models.

scholarly journals High-Resolution Satellite Analysis and Model Evaluation of Clouds and Radiation over the Mackenzie Basin Using AVHRR Data

1998 ◽  
Vol 11 (8) ◽  
pp. 1976-1996 ◽  
Author(s):  
Louis Garand ◽  
Serge Nadon
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Vertical Distribution ◽  
Model Evaluation ◽  
Cloud Fraction ◽  
The Arctic ◽  
Mackenzie Basin ◽  
Low Clouds ◽  
Cloud Tops ◽  
Satellite Analysis

Abstract Both the issues of high-resolution satellite analysis and model evaluation for a region centered on the Arctic Circle (60°–75°N) are addressed. Model cloud fraction, cloud height, and outgoing radiation are compared to corresponding satellite observations using a model-to-satellite approach (calculated radiances from model state). The dataset consists of forecasts run at 15-km resolution up to 30 h and nearly coincident Advanced Very High Resolution Radiometer (AVHRR) imagery during the Beaufort and Arctic Storm Experiment over the Mackenzie Basin for a monthly period in the fall of 1994. A cloud detection algorithm is designed for day and night application using the 11-μ channel of AVHRR along with available information on atmospheric and ground temperatures. The satellite and model estimates of cloud fraction are also compared to observations at 20 ground stations. A significant result of the validation is that the model has a higher frequency of low cloud tops and a lower frequency of midlevel cloud tops than the observations. On a monthly basis, the model 11-μ outgoing brightness temperature (TB) is consequently higher than observed by about 4.4 K at all forecast times, which corresponds to a deficit of 760 m in mean cloud-top height and about 10 W m−2 in outgoing flux at the top of the atmosphere. Possible errors in the parameterization of ice or water cloud emissivity are evaluated but ruled out as the dominant cause for the warm TB bias in the model. Rather, the problem is attributed to low clouds being trapped in the boundary layer, whereas high clouds appear to be reasonably well modeled. The role of thin ice clouds is further evaluated by comparing distributions of observed and modeled 11-μ minus 12-μ TB differences, DIF45 (channel 4 minus channel 5). The relationship between the true height of the clouds and the effective height observed by satellite is modeled from forecast outputs as a function of DIF45. The quality of daily estimates is evaluated from time series at various locations. The time series shows that there was a marked drop in DIF45 during the month, which is attributed to a decrease in the occurrence of cirrus clouds. Finally, the diurnal cycle of TB and cloud fraction is found to be relatively large with average monthly 0600–1800 UTC TB differences of both signs of the order of 4–8 K in broad sectors and cloud fraction differences of 10%–30%. Where low clouds prevail, the cloud fraction tends to decrease at night and TB increases. Overall, model–observation differences are dominated by differences in the vertical distribution of clouds. A reduction of this effect implies a modification of the “preferred” model climatology in terms of its vertical distribution of humidity and cloud water.

scholarly journals Ozone loss derived from balloon-borne tracer measurements and the SLIMCAT CTM

2004 ◽  
Vol 4 (6) ◽  
pp. 7089-7120 ◽  
Author(s):  
A. D. Robinson ◽  
G. A. Millard ◽  
F. Danis ◽  
M. Guirlet ◽  
N. R. P. Harris ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
Reasonable Agreement ◽  
The Arctic ◽  
Data Sets ◽  
Gas Chromatograph ◽  
Ozone Loss ◽  
Empirical Estimates ◽  
Vertical Distributions ◽  
Good Agreement

Abstract. Balloon-borne measurements of CFC-11 (on flights of the DIRAC in situ gas chromatograph and the DESCARTES grab sampler), ClO and O3 were made during the 1999/2000 winter as part of the SOLVE-THESEO 2000 campaign. Here we present the CFC-11 data from nine flights and compare them first with data from other instruments which flew during the campaign and then with the vertical distributions calculated by the SLIMCAT 3-D CTM. We calculate ozone loss inside the Arctic vortex between late January and early March using the relation between CFC-11 and O3 measured on the flights, the peak ozone loss (1200 ppbv) occurs in the 440–470 K region in early March in reasonable agreement with other published empirical estimates. There is also a good agreement between ozone losses derived from three independent balloon tracer data sets used here. The magnitude and vertical distribution of the loss derived from the measurements is in good agreement with the loss calculated from SLIMCAT over Kiruna for the same days.

scholarly journals Ozone loss derived from balloon-borne tracer measurements in the 1999/2000 Arctic winter

2005 ◽  
Vol 5 (5) ◽  
pp. 1423-1436 ◽  
Author(s):  
A. D. Robinson ◽  
G. A. Millard ◽  
F. Danis ◽  
M. Guirlet ◽  
N. R. P. Harris ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
Reasonable Agreement ◽  
The Arctic ◽  
Data Sets ◽  
Gas Chromatograph ◽  
Ozone Loss ◽  
Empirical Estimates ◽  
Vertical Distributions ◽  
Good Agreement

Abstract. Balloon-borne measurements of CFC11 (from the DIRAC in situ gas chromatograph and the DESCARTES grab sampler), ClO and O3 were made during the 1999/2000 Arctic winter as part of the SOLVE-THESEO 2000 campaign, based in Kiruna (Sweden). Here we present the CFC11 data from nine flights and compare them first with data from other instruments which flew during the campaign and then with the vertical distributions calculated by the SLIMCAT 3D CTM. We calculate ozone loss inside the Arctic vortex between late January and early March using the relation between CFC11 and O3 measured on the flights. The peak ozone loss (~1200ppbv) occurs in the 440-470K region in early March in reasonable agreement with other published empirical estimates. There is also a good agreement between ozone losses derived from three balloon tracer data sets used here. The magnitude and vertical distribution of the loss derived from the measurements is in good agreement with the loss calculated from SLIMCAT over Kiruna for the same days.

scholarly journals Influence of the Arctic Oscillation on the vertical distribution of clouds as observed by the A-Train constellation of satellites

2012 ◽  
Vol 12 (4) ◽  
pp. 10305-10329 ◽  
Author(s):  
A. Devasthale ◽  
M. Tjernström ◽  
M. Caian ◽  
M. A. Thomas ◽  
B. H. Kahn ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
Large Scale ◽  
Arctic Oscillation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Dominant Mode ◽  
The Arctic ◽  
Dipole Structure ◽  
The Arctic Oscillation

Abstract. The main purpose of this study is to investigate the influence of the Arctic Oscillation (AO), the dominant mode of natural variability over the northerly high latitudes, on the spatial (horizontal and vertical) distribution of clouds in the Arctic. To that end, we use a suite of sensors onboard NASA's A-Train satellites that provide accurate observations of the distribution of clouds along with information on atmospheric thermodynamics. Data from three independent sensors are used (AIRS-AQUA, CALIOP-CALIPSO and CPR-CloudSAT) covering two time periods (winter half years of 2002–2011 and 2006–2011, respectively) along with data from the ERA-Interim reanalysis. We show that the zonal vertical distribution of cloud fraction anomalies averaged over 67° N–82°; N to a first approximation follows a dipole structure (referred to as "Greenland cloud dipole anomaly", GCDA), such that during the positive phase of the AO, positive and negative cloud anomalies are observed eastwards and westward of Greenland, respectively, while the opposite is true for the negative phase of AO. By investigating the concurrent meteorological conditions (temperature, humidity and winds), we show that differences in the meridional energy and moisture transport during the positive and negative phases of the AO and the associated thermodynamics are responsible for the conditions that are conducive for the formation of this dipole structure. All three satellite sensors broadly observe this large-scale GCDA despite differences in their sensitivities, spatio-temporal and vertical resolutions, and the available lengths of data records, indicating the robustness of the results. The present study also provides a compelling case to carry out process-based evaluation of global and regional climate models.

scholarly journals Vertical distribution of aerosols in dust storms during the Arctic winter

2020 ◽  
Author(s):  
Pavla Dagsson Waldhauserova ◽  
Jean-Baptiste Renard ◽  
Haraldur Olafsson ◽  
Damien Vignelles ◽  
Gwenaël Berthet ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
Polar Vortex ◽  
High Arctic ◽  
Dust Storms ◽  
Dust Aerosol ◽  
The Arctic ◽  
Vertical Distributions ◽  
Winter Dust ◽  
Glaciogenic Sediments ◽  
Mixed Phase Clouds

<p>High Latitude Dust (HLD) contributes 5% to the global dust budget, but HLD measurements are sparse. Iceland has the largest area of volcaniclastic sandy desert on Earth where dust is originating from volcanic, but also glaciogenic sediments. Total Icelandic desert areas cover 44,000 km<sup>2</sup> which makes Iceland the largest Arctic as well as European desert. Icelandic volcanic dust can be transported distances > 1700 km towards the Arctic and deposited on snow, ice and sea ice. It is estimated that about 7% of Icelandic dust can reach the high Arctic (N>80°). It is known that about 50% of Icelandic dust storms occurred during winter or subzero temperatures in the southern part of Iceland. The vertical distributions of dust aerosol in high atmospheric profiles during these winter storms and long-range transport of dust during polar vortex condition were unknown.</p><p>Dust observations from Iceland provide dust aerosol distributions during the Arctic winter for the first time, profiling dust storms as well as clean air conditions. Five winter dust storms were captured during harsh conditions.  Mean number concentrations during the non-dust flights were < 5 particles cm<sup>-3 </sup>for the particles 0.2-100 µm in diameter and > 40 particles cm<sup>-3</sup> during dust storms. A moderate dust storm with > 250 particles cm<sup>-3</sup> (2 km altitude) was captured on 10<sup>th</sup> January 2016 as a result of sediments suspended from glacial outburst flood Skaftahlaup in 2015. Similar particle number concentrations were reported previously in the Saharan air layer. Detected particle sizes were up to 20 µm close to the surface, up to 10 µm at 900 m altitude, up to 5 µm at 5 km altitude, and submicron at altitudes > 6 km.</p><p>Dust sources in the Arctic are active during the winter and produce large amounts of particulate matter dispersed over long distances and high altitudes. HLD contributes to Arctic air pollution and has the potential to influence ice nucleation in mixed-phase clouds and Arctic amplification.</p><p> </p><p>Reference:</p><p>Dagsson-Waldhauserova, P., Renard, J.-B., Olafsson, H., Vignelles, D., Berthet, G., Verdier, N., Duverger, V., 2019. Vertical distribution of aerosols in dust storms during the Arctic winter. <strong>Scientific Reports </strong>6, 1-11.</p>

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.

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