scholarly journals Shortwave Radiative Effect of Arctic Low-Level Clouds: Evaluation of Imagery-Derived Irradiance with Aircraft Observations

2019 ◽  
Author(s):  
Hong Chen ◽  
Sebastian Schmidt ◽  
Michael D. King ◽  
Galina Wind ◽  
Anthony Bucholtz ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Optical Thickness ◽  
Surface Albedo ◽  
Detection Threshold ◽  
The Arctic ◽  
Radiative Effect ◽  
Cloud Detection ◽  
Study Region ◽  
Low Level ◽  
Cloud Properties

Abstract. Cloud optical properties such as optical thickness along with surface albedo are important inputs for deriving the shortwave radiative effects of clouds from space-borne remote sensing. Owing to insufficient knowledge about the snow or ice surface in the Arctic, cloud detection and the retrieval products derived from passive remote sensing, such as from the Moderate Resolution Imaging Spectroradiometer (MODIS), are difficult to obtain with adequate accuracy – especially for low-level thin clouds, which are ubiquitous in the Arctic. This study aims at evaluating the spectral and broadband irradiance calculated from MODIS-derived cloud properties in the Arctic using aircraft measurements collected during the Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE), specifically using the upwelling and downwelling shortwave spectral and broadband irradiance measured by the Solar Spectral Flux Radiometer (SSFR) and the BroadBand Radiometer system (BBR). This entails the derivation of surface albedo from SSFR/BBR and camera imagery for heterogeneous surfaces in the marginal ice zone (MIZ), as well as subsequent measurement-model inter-comparisons in the presence of thin clouds. In addition to MODIS cloud retrievals and surface albedo from SSFR, we used temperature and humidity data from in-situ data and reanalysis (MERRA-2). The spectral surface albedo derived from the airborne radiometers is consistent with prior ground-based measurements, and adequately represents the surface variability for the study region and time period. Somewhat surprisingly, the primary error in MODIS-derived irradiance fields for this study stems from undetected clouds, rather than from the retrieved cloud properties. In our case studies, about 22 % of clouds remained undetected (cloud optical thickness less than 0.5). The radiative effect of clouds above the detection threshold was −40 W m−2 above cloud, and −39 W m−2 below the cloud layer, and the optical thickness from the MODIS "1621" cloud product was consistent with the reflected and transmitted irradiance observations. This study suggests that passive imagery cloud detection could be improved through a multi-pixel approach, that would make it more dependable in the Arctic. Regardless of the cloud retrieval method, there is a need for an operational imagery-based surface albedo product for the polar regions that adequately captures its temporal, spatial, and spectral variability to estimate cloud radiative effect from space-borne remote sensing.

scholarly journals The effect of low-level thin arctic clouds on shortwave irradiance: evaluation of estimates from spaceborne passive imagery with aircraft observations

2021 ◽  
Vol 14 (4) ◽  
pp. 2673-2697
Author(s):  
Hong Chen ◽  
Sebastian Schmidt ◽  
Michael D. King ◽  
Galina Wind ◽  
Anthony Bucholtz ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Optical Thickness ◽  
Surface Albedo ◽  
The Arctic ◽  
Cloud Detection ◽  
Radiative Effects ◽  
Study Region ◽  
Airborne Measurements ◽  
Low Level ◽  
Cloud Properties

Abstract. Cloud optical properties such as optical thickness along with surface albedo are important inputs for deriving the shortwave radiative effects of clouds from spaceborne remote sensing. Owing to insufficient knowledge about the snow or ice surface in the Arctic, cloud detection and the retrieval products derived from passive remote sensing, such as from the Moderate Resolution Imaging Spectroradiometer (MODIS), are difficult to obtain with adequate accuracy – especially for low-level thin clouds, which are ubiquitous in the Arctic. This study aims at evaluating the spectral and broadband irradiance calculated from MODIS-derived cloud properties in the Arctic using aircraft measurements collected during the Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE), specifically using the upwelling and downwelling shortwave spectral and broadband irradiance measured by the Solar Spectral Flux Radiometer (SSFR) and the BroadBand Radiometer system (BBR). This starts with the derivation of surface albedo from SSFR and BBR, accounting for the heterogeneous surface in the marginal ice zone (MIZ) with aircraft camera imagery, followed by subsequent intercomparisons of irradiance measurements and radiative transfer calculations in the presence of thin clouds. It ends with an attribution of any biases we found to causes, based on the spectral dependence and the variations in the measured and calculated irradiance along the flight track. The spectral surface albedo derived from the airborne radiometers is consistent with prior ground-based and airborne measurements and adequately represents the surface variability for the study region and time period. Somewhat surprisingly, the primary error in MODIS-derived irradiance fields for this study stems from undetected clouds, rather than from the retrieved cloud properties. In our case study, about 27 % of clouds remained undetected, which is attributable to clouds with an optical thickness of less than 0.5. We conclude that passive imagery has the potential to accurately predict shortwave irradiances in the region if the detection of thin clouds is improved. Of at least equal importance, however, is the need for an operational imagery-based surface albedo product for the polar regions that adequately captures its temporal, spatial, and spectral variability to estimate cloud radiative effects from spaceborne remote sensing.

scholarly journals Radiative Effect of Clouds at Ny-Ålesund, Svalbard, as Inferred from Ground-Based Remote Sensing Observations

2020 ◽  
Vol 59 (1) ◽  
pp. 3-22 ◽  
Author(s):  
Kerstin Ebell ◽  
Tatiana Nomokonova ◽  
Marion Maturilli ◽  
Christoph Ritter
Keyword(s):  
Remote Sensing ◽  
The Arctic ◽  
Radiative Effect ◽  
Liquid Water Path ◽  
Ice Clouds ◽  
Surface Warming ◽  
Clear Sky ◽  
Cloud Properties ◽  
Cloud Radiative Effect ◽  
The Difference

AbstractFor the first time, the cloud radiative effect (CRE) has been characterized for the Arctic site Ny-Ålesund, Svalbard, Norway, including more than 2 years of data (June 2016–September 2018). The cloud radiative effect, that is, the difference between the all-sky and equivalent clear-sky net radiative fluxes, has been derived based on a combination of ground-based remote sensing observations of cloud properties and the application of broadband radiative transfer simulations. The simulated fluxes have been evaluated in terms of a radiative closure study. Good agreement with observed surface net shortwave (SW) and longwave (LW) fluxes has been found, with small biases for clear-sky (SW: 3.8 W m−2; LW: −4.9 W m−2) and all-sky (SW: −5.4 W m−2; LW: −0.2 W m−2) situations. For monthly averages, uncertainties in the CRE are estimated to be small (~2 W m−2). At Ny-Ålesund, the monthly net surface CRE is positive from September to April/May and negative in summer. The annual surface warming effect by clouds is 11.1 W m−2. The longwave surface CRE of liquid-containing cloud is mainly driven by liquid water path (LWP) with an asymptote value of 75 W m−2 for large LWP values. The shortwave surface CRE can largely be explained by LWP, solar zenith angle, and surface albedo. Liquid-containing clouds (LWP > 5 g m−2) clearly contribute most to the shortwave surface CRE (70%–98%) and, from late spring to autumn, also to the longwave surface CRE (up to 95%). Only in winter are ice clouds (IWP > 0 g m−2; LWP < 5 g m−2) equally important or even dominating the signal in the longwave surface CRE.

scholarly journals Retrieved Optical Thickness for Analyzing The Aerosol and Cloud Properties Using Lidar Remote Sensing

2012 ◽  
Vol 13 (1) ◽  
pp. 7
Author(s):  
Syamsir Dewang
Keyword(s):  
Remote Sensing ◽  
Optical Thickness ◽  
Reference Data ◽  
Single Scattering ◽  
Lidar Data ◽  
Night Time ◽  
Cloud Properties ◽  
Tropical Area ◽  
Signal Simulation ◽  
The One

The lidar remote sensing is the one important application to observe the aerosol and cloud of the atmosphere. Themicropulse lidar (MPL) return signals were studied in the tropical area. In this investigation, the single scatteringis analyzed by the physical properties of aerosol and cloud. The signal simulation of the single scattering predictsthe maximum optical thickness by saturation. It was observed that saturation optical thickness from the lidarsignal depends on the variation of extinction coefficient. This simulation is compared by the optical thicknessestimation from the lidar data. The MPL data (at wavelength of 523 nm) was determined, and the sky radiometer (atwavelength 500 nm) was used as reference data. The maximum optical thickness of lidar was 2.6 at night time,and the maximum optical depth of lidar and sky radiometer data on the same day were 2.25 and 1.7, respectively.

Radiative forcing over the Arctic of aerosols from the August 2017 Canadian and Greenlandic wildfires

2021 ◽  
Author(s):  
Filippo Calì Quaglia ◽  
Daniela Meloni ◽  
Alcide Giorgio di Sarra ◽  
Tatiana Di Iorio ◽  
Virginia Ciardini ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Radiative Forcing ◽  
Solar Zenith Angle ◽  
Surface Albedo ◽  
High Arctic ◽  
The Arctic ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Aerosol Layer ◽  
Radiative Effect

&lt;p&gt;Extended and intense wildfires occurred in Northern Canada and, unexpectedly, on the Greenlandic West coast during summer 2017. The thick smoke plume emitted into the atmosphere was transported to the high Arctic, producing one of the largest impacts ever observed in the region. Evidence of Canadian and Greenlandic wildfires was recorded at the Thule High Arctic Atmospheric Observatory (THAAO, 76.5&amp;#176;N, 68.8&amp;#176;W, www.thuleatmos-it.it) by a suite of instruments managed by ENEA, INGV, Univ. of Florence, and NCAR. Ground-based observations of the radiation budget have allowed quantification of the surface radiative forcing at THAAO.&amp;#160;&lt;/p&gt;&lt;p&gt;Excess biomass burning chemical tracers such as CO, HCN, H2CO, C2H6, and NH3 were&amp;#160; measured in the air column above Thule starting from August 19 until August 23. The aerosol optical depth (AOD) reached a peak value of about 0.9 on August 21, while an enhancement of wildfire compounds was&amp;#160; detected in PM10. The measured shortwave radiative forcing was -36.7 W/m2 at 78&amp;#176; solar zenith angle (SZA) for AOD=0.626.&lt;/p&gt;&lt;p&gt;MODTRAN6.0 radiative transfer model (Berk et al., 2014) was used to estimate the aerosol radiative effect and the heating rate profiles at 78&amp;#176; SZA. Measured temperature profiles, integrated water vapour, surface albedo, spectral AOD and aerosol extinction profiles from CALIOP onboard CALIPSO were used as model input. The peak&amp;#160; aerosol heating rate (+0.5 K/day) was&amp;#160; reached within the aerosol layer between 8 and 12 km, while the maximum radiative effect (-45.4 W/m2) is found at 3 km, below the largest aerosol layer.&lt;/p&gt;&lt;p&gt;The regional impact of the event that occurred on August 21 was investigated using a combination of atmospheric radiative transfer modelling with measurements of AOD and ground surface albedo from MODIS. The aerosol properties used in the radiative transfer model were constrained by in situ measurements from THAAO. Albedo data over the ocean have been obtained from Jin et al. (2004). Backward trajectories produced through HYSPLIT simulations (Stein et al., 2015) were also employed to trace biomass burning plumes.&lt;/p&gt;&lt;p&gt;The radiative forcing efficiency (RFE) over land and ocean was derived, finding values spanning from -3 W/m2 to -132 W/m2, depending on surface albedo and solar zenith angle. The fire plume covered a vast portion of the Arctic, with large values of the daily shortwave RF (&lt; -50 W/m2) lasting for a few days. This large amount of aerosol is expected to influence cloud properties in the Arctic, producing significant indirect radiative effects.&lt;/p&gt;

scholarly journals Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing

2017 ◽  
Vol 10 (9) ◽  
pp. 3215-3230 ◽  
Author(s):  
André Ehrlich ◽  
Eike Bierwirth ◽  
Larysa Istomina ◽  
Manfred Wendisch
Keyword(s):  
Remote Sensing ◽  
Grain Size ◽  
Sea Ice ◽  
Optical Thickness ◽  
Liquid Water ◽  
Retrieval Algorithm ◽  
Continuous Transition ◽  
Cloud Properties ◽  
Cloud Optical Thickness ◽  
The Impact

Abstract. The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow). Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius reff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size reff, S. Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and reff, C for liquid water clouds. In general, the impact of uncertainties of reff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved reff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for reff, C. In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters (τ, reff, C, reff, S) and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ1 = 1040 nm (sensitive to reff, S), λ2 = 1650 nm (sensitive to τ), and λ3 = 2100 nm (sensitive to reff, C) are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART) during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012) were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice edge are analysed. The retrieved values of τ, reff, C, and reff, S show a continuous transition of cloud properties across snow-covered sea ice and open water and are consistent with estimates based on satellite data. It is shown that the uncertainties of the trispectral retrieval increase for high values of τ, and low reff, S but nevertheless allow the effective snow grain size in cloud-covered areas to be estimated.

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 Clouds over the summertime Sahara: an evaluation of Met Office retrievals from Meteosat Second Generation using airborne remote sensing

2017 ◽  
Vol 17 (9) ◽  
pp. 5789-5807 ◽  
Author(s):  
John C. Kealy ◽  
Franco Marenco ◽  
John H. Marsham ◽  
Luis Garcia-Carreras ◽  
Pete N. Francis ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Second Generation ◽  
High Surface ◽  
Cloud Amount ◽  
Limiting Factors ◽  
Cloud Detection ◽  
Airborne Remote Sensing ◽  
Horizontal Extent ◽  
Cloud Properties ◽  
Cloud Mask

Abstract. Novel methods of cloud detection are applied to airborne remote sensing observations from the unique Fennec aircraft dataset, to evaluate the Met Office-derived products on cloud properties over the Sahara based on the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on-board the Meteosat Second Generation (MSG) satellite. Two cloud mask configurations are considered, as well as the retrievals of cloud-top height (CTH), and these products are compared to airborne cloud remote sensing products acquired during the Fennec campaign in June 2011 and June 2012. Most detected clouds (67 % of the total) have a horizontal extent that is smaller than a SEVIRI pixel (3 km  ×  3 km). We show that, when partially cloud-contaminated pixels are included, a match between the SEVIRI and aircraft datasets is found in 80 ± 8 % of the pixels. Moreover, under clear skies the datasets are shown to agree for more than 90 % of the pixels. The mean cloud field, derived from the satellite cloud mask acquired during the Fennec flights, shows that areas of high surface albedo and orography are preferred sites for Saharan cloud cover, consistent with published theories. Cloud-top height retrievals however show large discrepancies over the region, which are ascribed to limiting factors such as the cloud horizontal extent, the derived effective cloud amount, and the absorption by mineral dust. The results of the CTH analysis presented here may also have further-reaching implications for the techniques employed by other satellite applications facilities across the world.

scholarly journals Improved cloud detection over sea ice and snow during Arctic summer using MERIS data

2020 ◽  
Vol 13 (12) ◽  
pp. 6459-6472
Author(s):  
Larysa Istomina ◽  
Henrik Marks ◽  
Marcus Huntemann ◽  
Georg Heygster ◽  
Gunnar Spreen
Keyword(s):  
Remote Sensing ◽  
Sea Ice ◽  
Remote Sensing Data ◽  
The Arctic ◽  
Cloud Detection ◽  
High Quality ◽  
Melt Pond ◽  
Resolution Imaging ◽  
Cloud Mask ◽  
Cloud Screening

Abstract. The historic MERIS (Medium Resolution Imaging Spectrometer) sensor on board Envisat (Environmental Satellite, operation 2002–2012) provides valuable remote sensing data for the retrievals of summer sea ice in the Arctic. MERIS data together with the data of recently launched successor OLCI (Ocean and Land Colour Instrument) on board Sentinel 3A and 3B (2016 onwards) can be used to assess the long-term change of the Arctic summer sea ice. An important prerequisite to a high-quality remote sensing dataset is an accurate separation of cloudy and clear pixels to ensure lowest cloud contamination of the resulting product. The presence of 15 visible and near-infrared spectral channels of MERIS allows high-quality retrievals of sea ice albedo and melt pond fraction, but it makes cloud screening a challenge as snow, sea ice and clouds have similar optical features in the available spectral range of 412.5–900 nm. In this paper, we present a new cloud screening method MECOSI (MERIS Cloud Screening Over Sea Ice) for the retrievals of spectral albedo and melt pond fraction (MPF) from MERIS. The method utilizes all 15 MERIS channels, including the oxygen A absorption band. For the latter, a smile effect correction has been developed to ensure high-quality screening throughout the whole swath. A total of 3 years of reference cloud mask from AATSR (Advanced Along-Track Scanning Radiometer) (Istomina et al., 2010) have been used to train the Bayesian cloud screening for the available limited MERIS spectral range. Whiteness and brightness criteria as well as normalized difference thresholds have been used as well. The comparison of the developed cloud mask to the operational AATSR and MODIS (Moderate Resolution Imaging Spectroradiometer) cloud masks shows a considerable improvement in the detection of clouds over snow and sea ice, with about 10 % false clear detections during May–July and less than 5 % false clear detections in the rest of the melting season. This seasonal behavior is expected as the sea ice surface is generally brighter and more challenging for cloud detection in the beginning of the melting season. The effect of the improved cloud screening on the MPF–albedo datasets is demonstrated on both temporal and spatial scales. In the absence of cloud contamination, the time sequence of MPFs displays a greater range of values throughout the whole summer. The daily maps of the MPF now show spatially uniform values without cloud artifacts, which were clearly visible in the previous version of the dataset. The developed cloud screening routine can be applied to address cloud contamination in remote sensing data over sea ice. The resulting cloud mask for the MERIS operating time, as well as the improved MPF–albedo datasets for the Arctic region, is available at https://www.seaice.uni-bremen.de/start/ (Istomina et al., 2017).

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