Arctic low-level clouds and their importance for radiative transfer simulations

2021 ◽  
Author(s):  
Hannes Griesche ◽  
Carola Barrientos Velasco ◽  
Patric Seifert
Keyword(s):  
Remote Sensing ◽  
Radiative Transfer ◽  
Liquid Water ◽  
Remote Sensing Data ◽  
The Arctic ◽  
Liquid Water Path ◽  
Low Level ◽  
Cloud Radar ◽  
Microphysical Properties ◽  
Water Detection

<p>The observation of low-level stratocumulus cloud decks in the Arctic poses challenges to ground-based remote sensing. These clouds frequently occur during summer below the lowest range gate of common zenith-pointing cloud radar instruments, like the KAZR and the Mira-35. In addition, the optical thickness of these low-level clouds often do cause a complete attenuation of the lidar beam. For remote-sensing instrument synergy retrievals, as Cloudnet (Illingworth, 2007) or ARSCL (Active Remote Sensing of Clouds, Shupe, 2007), liquid-water detection in clouds is usually based on lidar backscatter. Thus, a complete attenuation can cause misclassification of mixed-phase clouds as pure-ice clouds. Moreover, the missing cloud radar information makes it difficult to derive the cloud microphysical properties, as most common retrievals are based on cloud radar reflectivity.</p> <p>A new low-level stratus detection mask (Griesche, 2020) was used to detect these clouds. The liquid-water cloud microphysical properties were derived by a simple but effective analysis of the liquid-water path. This approach was applied to remote-sensing data from a shipborne expedition performed in the Arctic summer 2017. The values calculated by applying the adjusted method improve the results of radiative transfer simulations yielding the determination of radiative closure.</p> <p> </p> <p> </p> <p>Illingworth et al. (2007). “Cloudnet”. BAMS.</p> <p>Shupe (2007). “A ground-based multisensor cloud phase classifier”. GRL.</p> <p>Griesche et al. (2020). “Application of the shipborne remote sensing supersite OCEANET for profiling of Arctic aerosols and clouds during Polarstern cruise PS106”. AMT.</p>

scholarly journals Effects of long-range aerosol transport on the microphysical properties of low-level liquid clouds in the Arctic

2016 ◽  
Vol 16 (7) ◽  
pp. 4661-4674 ◽  
Author(s):  
Quentin Coopman ◽  
Timothy J. Garrett ◽  
Jérôme Riedi ◽  
Sabine Eckhardt ◽  
Andreas Stohl
Keyword(s):  
Long Range ◽  
Liquid Water ◽  
Specific Humidity ◽  
The Arctic ◽  
Liquid Water Path ◽  
Arctic Clouds ◽  
Low Level ◽  
Microphysical Properties ◽  
Lower Tropospheric Stability ◽  
Pollution Concentrations

Abstract. The properties of low-level liquid clouds in the Arctic can be altered by long-range pollution transport to the region. Satellite, tracer transport model, and meteorological data sets are used here to determine a net aerosol–cloud interaction (ACInet) parameter that expresses the ratio of relative changes in cloud microphysical properties to relative variations in pollution concentrations while accounting for dry or wet scavenging of aerosols en route to the Arctic. For a period between 2008 and 2010, ACInet is calculated as a function of the cloud liquid water path, temperature, altitude, specific humidity, and lower tropospheric stability. For all data, ACInet averages 0.12 ± 0.02 for cloud-droplet effective radius and 0.16 ± 0.02 for cloud optical depth. It increases with specific humidity and lower tropospheric stability and is highest when pollution concentrations are low. Carefully controlling for meteorological conditions we find that the liquid water path of arctic clouds does not respond strongly to aerosols within pollution plumes. Or, not stratifying the data according to meteorological state can lead to artificially exaggerated calculations of the magnitude of the impacts of pollution on arctic clouds.

scholarly journals Implications of Limited Liquid Water Path on Static Mixing within Arctic Low-Level Clouds

2014 ◽  
Vol 53 (12) ◽  
pp. 2775-2789 ◽  
Author(s):  
Joseph Sedlar
Keyword(s):  
Mixed Layer ◽  
Liquid Water ◽  
Heat Budget ◽  
Single Layer ◽  
Specific Humidity ◽  
The Arctic ◽  
Liquid Water Path ◽  
Stable Layer ◽  
Water Path ◽  
Low Level

AbstractObservations of cloud properties and thermodynamics from two Arctic locations, Barrow, Alaska, and Surface Heat Budget of the Arctic (SHEBA), are examined. A comparison of in-cloud thermodynamic mixing characteristics for low-level, single-layer clouds from nearly a decade of data at Barrow and one full annual cycle over the sea ice at SHEBA is performed. These cloud types occur relatively frequently, evident in 27%–30% of all cloudy cases. To understand the role of liquid water path (LWP), or lack thereof, on static in-cloud mixing, cloud layers are separated into optically thin and optically thick LWP subclasses. Clouds with larger LWPs tend to have a deeper in-cloud mixed layer relative to optically thinner clouds. However, both cloud LWP subclasses are frequently characterized by an in-cloud stable layer above the mixed layer top. The depth of the stable layer generally correlates with an increased temperature gradient across the layer. This layer often contains a specific humidity inversion, but it is more frequently present when cloud LWP is optically thinner (LWP < 50 g m−2). It is suggested that horizontal thermodynamic advection plays a key role modifying the vertical extent of in-cloud mixing and likewise the depth of in-cloud stable layers. Furthermore, longwave atmospheric opacity above the cloud top is generally enhanced during cases with optically thinner clouds. Thermodynamic advection, cloud condensate distribution within the stable layer, and enhanced atmospheric radiation above the cloud are found to introduce a thermodynamic–radiative feedback that potentially modifies the extent of LWP and subsequent in-cloud mixing.

scholarly journals Satellite-based radiative forcing by light-absorbing particles in snow across the Northern Hemisphere

2021 ◽  
Vol 21 (1) ◽  
pp. 269-288
Author(s):  
Jiecan Cui ◽  
Tenglong Shi ◽  
Yue Zhou ◽  
Dongyou Wu ◽  
Xin Wang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Radiative Transfer ◽  
Northern Hemisphere ◽  
Radiative Forcing ◽  
Remote Sensing Data ◽  
The Arctic ◽  
Snow Albedo ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Earth’S Climate

Abstract. Snow is the most reflective natural surface on Earth and consequently plays an important role in Earth's climate. Light-absorbing particles (LAPs) deposited on the snow surface can effectively decrease snow albedo, resulting in positive radiative forcing. In this study, we used remote-sensing data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) and the Snow, Ice, and Aerosol Radiative (SNICAR) model to quantify the reduction in snow albedo due to LAPs before validating and correcting the data against in situ observations. We then incorporated these corrected albedo-reduction data in the Santa Barbara DISORT (Discrete Ordinate Radiative Transfer) Atmospheric Radiative Transfer (SBDART) model to estimate Northern Hemisphere radiative forcing except for midlatitude mountains in December–May for the period 2003–2018. Our analysis reveals an average corrected reduction in snow albedo (ΔαMODIS,correctedLAPs) of ∼ 0.021 under all-sky conditions, with daily radiative forcing (RFMODIS,dailyLAPs) values of ∼ 2.9 W m−2, over land areas with complete or near-complete snow cover and with little or no vegetation above the snow in the Northern Hemisphere. We also observed significant spatial variations in ΔαMODIS,correctedLAPs and RFMODIS,dailyLAPs, with the lowest respective values (∼ 0.016 and ∼ 2.6 W m−2) occurring in the Arctic and the highest (∼ 0.11 and ∼ 12 W m−2) in northeastern China. From MODIS retrievals, we determined that the LAP content of snow accounts for 84 % and 70 % of the spatial variability in albedo reduction and radiative forcing, respectively. We also compared retrieved radiative forcing values with those of earlier studies, including local-scale observations, remote-sensing retrievals, and model-based estimates. Ultimately, estimates of radiative forcing based on satellite-retrieved data are shown to represent true conditions on both regional and global scales.

scholarly journals Application of the shipborne remote sensing supersite OCEANET for profiling of Arctic aerosols and clouds during Polarstern cruise PS106

2019 ◽  
Author(s):  
Hannes Jascha Griesche ◽  
Patric Seifert ◽  
Albert Ansmann ◽  
Holger Baars ◽  
Carola Barrientos Velasco ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Sea Level ◽  
Microwave Radiometer ◽  
Value Added ◽  
High Arctic ◽  
Surface Processes ◽  
The Arctic ◽  
Target Classification ◽  
Cloud Radar ◽  
Microphysical Properties

Abstract. From 25 May to 21 July 2017, the research vessel Polarstern performed the cruise PS106 to the high Arctic in the region north and northeast of Svalbard. PS106 contributed observations for the initiative "Arctic Amplification: Climate Relevant Atmospheric and Surface Processes and Feedback Mechanisms (AC)3" which involves numerous projects aiming on understanding the role of atmospheric and surface processes in the ongoing rapid changes in the Arctic climate. As one of the central facilities of (AC)3, the mobile remote sensing platform OCEANET was deployed aboard Polarstern. Within a single container, OCEANET houses state-of-the-art remote sensing equipment, including a multi-wavelength Raman polarization lidar PollyXT and a 14-channel microwave radiometer HATPRO. For the cruise PS106 the measurements were supplemented by a motion-stabilized 35-GHz cloud radar Mira-35. This paper describes the treatment of technical challenges which were immanent during the deployment of OCEANET in the high Arctic. This includes the description of the motion stabilization of the cloud radar Mira-35 to ensure vertical-stare observations aboard the moving Polarstern. Also, low-level clouds and the presence of fog frequently prevented a continuous analysis of cloud conditions from synergies of lidar and radar within Cloudnet, because the technically determined lowest detection height of Mira-35 was 165m above sea level. To overcome this obstacle, an approach for identification of the cloud presence solely based on data from the near-field receiver of PollyXT at heights from 50m and 165m above sea level is presented. In addition, we provide an overview of the data processing chain of the OCEANET observations and demonstrate case studies of aerosol and cloud studies to introduce the capabilities of the dataset. The retrieval of aerosol optical and microphysical properties from the observations of PollyXT is presented by means of observations performed during the ice floe camp. Synergies between the remote sensing instruments and auxiliary observations from aboard Polarstern were analyzed by means of Cloudnet which provides as primary output a target classification mask. This target classification is the basis for value-added products such as liquid- and ice-cloud microphysical properties, cloud dynamics which can in subsequent steps be used as input for the investigation of cloud microphysical processes, radiative transfer calculations, or model evaluation. To this end, new approaches for ice crystal effective radius and eddy dissipation rates have been implemented into Cloudnet.

scholarly journals Stability dependent increases in liquid water with droplet number in the Arctic

2021 ◽  
Author(s):  
Rebecca Jonette Murray-Watson ◽  
Edward Gryspeerdt
Keyword(s):  
Liquid Water ◽  
Cloud Droplet ◽  
Surface Energy Budget ◽  
Radiative Properties ◽  
The Arctic ◽  
Polar Regions ◽  
Liquid Water Path ◽  
Arctic Clouds ◽  
Microphysical Properties ◽  
The Relationship

Abstract. The effects of aerosols on cloud microphysical properties are a large source of uncertainty when assessing anthropogenic climate change. The aerosol-cloud relationship is particularly unclear in high-latitude polar regions due to a limited number of observations. Cloud liquid water path (LWP) is an important control on cloud radiative properties, particularly in the Arctic, where clouds play a central role in the surface energy budget. Therefore, understanding how aerosols may alter cloud LWP is important, especially as aerosol sources such as industry and shipping move further north in a warming Arctic. Using satellite data, this work investigates the effects of aerosols on liquid Arctic clouds over open ocean by considering the relationship between cloud droplet number concentration (Nd) and LWP, an important component of the aerosol-LWP relationship. The LWP response to Nd varies significantly across the region, with increases in LWP with Nd observed at very high latitudes in multiple satellite datasets, with this positive signal observed most strongly during the summer months. This result is in contrast to the negative response typically seen in global satellite studies and previous work on Arctic clouds showing little LWP response to aerosols. The lower tropospheric stability (LTS) was found to be the driving force behind the spatial variations in LWP response, strongly influencing the sign and magnitude of the Nd-LWP relationship, with increases in LWP in high stability environments. The influence of humidity varied depending on the stability, with little impact at low LTS but a strong influence at high. The background Nd state does not seem to dominate the LWP response, despite the non-linearities in the relationship. As the LTS is projected to decrease in a future, warmer Arctic, these results show that increases may produce lower cloud water paths, offsetting their shortwave cooling effect.

scholarly journals Ground-based remote sensing of thin clouds in the Arctic

2012 ◽  
Vol 5 (6) ◽  
pp. 8653-8699 ◽  
Author(s):  
T. J. Garrett ◽  
C. Zhao
Keyword(s):  
Water Vapor ◽  
Thermal Emission ◽  
Stratospheric Ozone ◽  
Microwave Radiometer ◽  
Single Layer ◽  
Primary Source ◽  
The Arctic ◽  
Liquid Water Path ◽  
Water Path ◽  
Microphysical Properties

Abstract. This paper describes a method for using interferometer measurements of downwelling thermal radiation to retrieve the properties of single-layer clouds. Cloud phase is determined from ratios of thermal emission in three "micro-windows" where absorption by water vapor is particularly small. Cloud microphysical and optical properties are retrieved from thermal emission in two micro-windows, constrained by the transmission through clouds of stratospheric ozone emission. Assuming a cloud does not approximate a blackbody, the estimated 95% confidence retrieval errors in effective radius, visible optical depth, number concentration, and water path are, respectively, 10%, 20%, 38% (55% for ice crystals), and 16%. Applied to data from the Atmospheric Radiation Measurement program (ARM) North Slope of Alaska – Adjacent Arctic Ocean (NSA-AAO) site near Barrow, Alaska, retrievals show general agreement with ground-based microwave radiometer measurements of liquid water path. Compared to other retrieval methods, advantages of this technique include its ability to characterize thin clouds year round, that water vapor is not a primary source of retrieval error, and that the retrievals of microphysical properties are only weakly sensitive to retrieved cloud phase. The primary limitation is the inapplicability to thicker clouds that radiate as blackbodies.

scholarly journals Analysis of Sentinel-2 and RapidEye for Retrieval of Leaf Area Index in a Saltmarsh Using a Radiative Transfer Model

2019 ◽  
Vol 11 (6) ◽  
pp. 671 ◽  
Author(s):  
Roshanak Darvishzadeh ◽  
Tiejun Wang ◽  
Andrew Skidmore ◽  
Anton Vrieling ◽  
Brian O’Connor ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Radiative Transfer ◽  
Leaf Area Index ◽  
Plant Traits ◽  
Remote Sensing Data ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Area Index ◽  
Field Campaigns ◽  
Sentinel 2

The Sentinel satellite fleet of the Copernicus Programme offers new potential to map and monitor plant traits at fine spatial and temporal resolutions. Among these traits, leaf area index (LAI) is a crucial indicator of vegetation growth and an essential variable in biodiversity studies. Numerous studies have shown that the radiative transfer approach has been a successful method to retrieve LAI from remote-sensing data. However, the suitability and adaptability of this approach largely depend on the type of remote-sensing data, vegetation cover and the ecosystem studied. Saltmarshes are important wetland ecosystems threatened by sea level rise among other human- and animal-induced changes. Therefore, monitoring their vegetation status is crucial for their conservation, yet few LAI assessments exist for these ecosystems. In this study, the retrieval of LAI in a saltmarsh ecosystem is examined using Sentinel-2 and RapidEye data through inversion of the PROSAIL radiative transfer model. Field measurements of LAI and some other plant traits were obtained during two succeeding field campaigns in July 2015 and 2016 on the saltmarsh of Schiermonnikoog, a barrier island of the Netherlands. RapidEye (2015) and Sentinel-2 (2016) data were acquired concurrent to the time of the field campaigns. The broadly employed PROSAIL model was inverted using two look-up tables (LUTs) generated in the spectral band’s settings of the two sensors and in which each contained 500,000 records. Different solutions from the LUTs, as well as, different Sentinel-2 spectral subsets were considered to examine the LAI retrieval. Our results showed that generally the LAI retrieved from Sentinel-2 had higher accuracy compared to RapidEye-retrieved LAI. Utilising the mean of the first 10 best solutions from the LUTs resulted in higher R2 (0.51 and 0.59) and lower normalised root means square error (NRMSE) (0.24 and 0.16) for both RapidEye and Sentinel-2 data respectively. Among different Sentinel-2 spectral subsets, the one comprised of the four near-infrared (NIR) and shortwave infrared (SWIR) spectral bands resulted in higher estimation accuracy (R2 = 0.44, NRMSE = 0.21) in comparison to using other studied spectral subsets. The results demonstrated the feasibility of broadband multispectral sensors, particularly Sentinel-2 for retrieval of LAI in the saltmarsh ecosystem via inversion of PROSAIL. Our results highlight the importance of proper parameterisation of radiative transfer models and capacity of Sentinel-2 spectral range and resolution, with impending high-quality global observation aptitude, for retrieval of plant traits at a global scale.

Separating Cloud and Drizzle Signals in Radar Doppler Spectra Using a Parametric Time Domain Method

2020 ◽  
Vol 37 (9) ◽  
pp. 1669-1680
Author(s):  
Shashank S. Joshil ◽  
Cuong M. Nguyen ◽  
V. Chandrasekar ◽  
J. Christine Chiu ◽  
Yann Blanchard
Keyword(s):  
Remote Sensing ◽  
Time Domain ◽  
Marine Boundary Layer ◽  
Time Domain Method ◽  
Radar Signal ◽  
Liquid Water Path ◽  
Microphysical Properties ◽  
Observation Volume ◽  
Domain Method ◽  
The Time Domain

AbstractThe ability to separate cloud and drizzle returns in active remote sensing observations is important for understanding the microphysics of clouds and precipitation. Yet, robust separations remain challenging in radar remote sensing. Prior methods for cloud and drizzle separation for radar observations use the properties of the Doppler spectra such as skewness. However, these methods have challenges when the drizzle becomes dominant in the observation volume. This paper presents a parametric time domain method (PTDM) that separates cloud and drizzle using the Doppler spectra measurements without assuming any prior properties of cloud and drizzle. The advantage of PTDM is that it can estimate the signal properties in the time domain and can obtain the cloud and drizzle estimates simultaneously. Based on our radar signal simulations, the uncertainty in estimated power and velocity from PTDM are within 2 dB and 0.02 m s−1, respectively. We have also evaluated the PTDM algorithm using observations from the Atmospheric Radiation Measurement (ARM) Program W-band cloud radar in the Clouds, Aerosols, and Precipitation in the Marine Boundary Layer (CAP-MBL) campaign at the Azores in 2009–10. Two cases corresponding to light and moderate drizzling conditions are considered for the study. The statistics of the estimates obtained show that the PTDM method performs well in separating the cloud and drizzle returns. Finally, the estimated cloud and drizzle reflectivity from PTDM were used to retrieve their corresponding microphysical properties, showing that the retrieved liquid water path agrees to 25 g m−2 with the benchmark microwave method.

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