Airborne measurements of directional reflectivity over the Arctic marginal sea ice zone

Becker, Sebastian; Ehrlich, André; Jäkel, Evelyn; Carlsen, Tim; Schäfer, Michael; Wendisch, Manfred

doi:10.5194/amt-15-2939-2022

Cited by 6 publications

(5 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Combining the downward irradiance measured by SMART and the radiances from the fish-eye camera allows the calculation of the hemispherical-directional reflectance factor (HDRF) at flight altitude. Following the method described by 58 , the HDRFs of sea ice and open-ocean surfaces can be separated employing a sequence of surface images. Further, the Nikon data were used to classify the sea ice and ocean surface into open water, sea ice, and melt ponds based on color thresholds.…”

Section: Cgr-4mentioning

confidence: 99%

MOSAiC-ACA and AFLUX - Arctic airborne campaigns characterizing the exit area of MOSAiC

et al. 2022

Self Cite

View full text Add to dashboard Cite

Two airborne field campaigns focusing on observations of Arctic mixed-phase clouds and boundary layer processes and their role with respect to Arctic amplification have been carried out in spring 2019 and late summer 2020 over the Fram Strait northwest of Svalbard. The latter campaign was closely connected to the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. Comprehensive datasets of the cloudy Arctic atmosphere have been collected by operating remote sensing instruments, in-situ probes, instruments for the measurement of turbulent fluxes of energy and momentum, and dropsondes on board the AWI research aircraft Polar 5. In total, 24 flights with 111 flight hours have been performed over open ocean, the marginal sea ice zone, and sea ice. The datasets follow documented methods and quality assurance and are suited for studies on Arctic mixed-phase clouds and their transformation processes, for studies with a focus on Arctic boundary layer processes, and for satellite validation applications. All datasets are freely available via the world data center PANGAEA.

show abstract

Section: Cgr-4mentioning

confidence: 99%

MOSAiC-ACA and AFLUX - Arctic airborne campaigns characterizing the exit area of MOSAiC

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…Additionally, the surface brightness temperature and the sea ice concentration were derived from measurements of a nadir-directed Kelvin infrared radiation thermometer (KT-19, sampling frequency of 20 Hz), and a three-channel digital camera equipped with a 180 • fish-eye lens (sampling frequency of 1/6 Hz). The individual pixels of the radiance-calibrated images of the fish-eye camera were classified into the different surface types based on their reflection characteristics (Becker et al, 2022), in order to derive the cosine-weighted surface type fraction of each image. Based on the transmissivity of the clouds, which is the fraction of the downward irradiances measured in mostly cloudy atmospheric conditions and simulated for cloud-free conditions, an equivalent LWP was retrieved using the method of Stapf et al (2020) and assuming clouds with a droplet r eff of 8 µm.…”

Section: Airborne Campaigns and Instrumentationmentioning

confidence: 99%

“…Note that for the low-level observations, the MIZ comprises all observations with f ice between 0.05 and 0.95 and, thus, deviates from the MIZ definition of Strong and Rigor (2013), where f ice is between 0.15 and 0.8. These modified thresholds are motivated by the strong impact of the surface type on the surface radiative properties, which significantly changes already for small fractions of sea ice or open ocean and requires a more rigorous separation of the MIZ (e. g., Becker et al, 2022).…”

Section: Sea Ice Situation During the Campaignsmentioning

confidence: 99%

Airborne observations of the surface cloud radiative effect during different seasons over sea ice and open ocean in the Fram Strait

Becker

Ehrlich

Schäfer

et al. 2023

Preprint

View full text Add to dashboard Cite

Abstract. This study analyzes the surface cloud radiative effect (CRE) obtained during airborne observations of three campaigns in the Arctic north-west of Svalbard. The surface CRE quantifies the potential of clouds to modify the radiative energy budget of the surface and is calculated by combining broadband radiation measurements during low-level flight sections in mostly cloudy conditions with radiative transfer simulations of cloud-free conditions. The significance of surface albedo changes due to the presence of clouds is demonstrated and this effect is considered in the cloud-free simulations. The observations are discussed with respect to differences of the CRE between sea ice and open ocean surfaces, and between the seasonally different campaigns. The results indicate that the CRE depends on both cloud, illumination, surface, and thermodynamic properties. The solar and thermal-infrared (TIR) component of the CRE are analyzed separately and in combination. The inter-campaign differences of the solar CRE are dominated by the seasonal cycle of the solar zenith angle, with the largest cooling effect in summer. The lower surface albedo causes a larger solar cooling effect over open ocean than over sea ice, which amounts to −259 W m−2 (−108 W m−2) and −65 W m−2 (−17 W m−2), respectively, during summer (spring). Independent of campaign and surface type, the TIR CRE is only weakly variable and shows values around 75 W m−2. In total, clouds show a cooling effect over open ocean during all campaigns. In contrast, clouds over sea ice exert a warming effect to the surface, which neutralizes during mid-summer. Given the seasonal cycle of the sea ice distribution, these results imply that clouds in the Fram Strait region cool the surface during the sea ice minimum in late summer, while they warm the surface during the sea ice maximum in spring.

show abstract

“…The directional reflectance of snow-covered sea ice has also been measured or modelled (e.g. Arnold et al, 2002;Li and Zhou, 2004;Becker et al, 2022;Goyens et al, 2018), but the characterisation of the directional reflectance of bare sea ice in the literature remains scarce. Jin and Simpson (1999) calculated the anisotropy reflectance factor (ARF) for bare sea ice.…”

Section: Introductionmentioning

confidence: 99%

The effects of surface roughness on the calculated, spectral, conical–conical reflectance factor as an alternative to the bidirectional reflectance distribution function of bare sea ice

Lamare

Hedley²,

King

2023

The Cryosphere

View full text Add to dashboard Cite

Abstract. The conical–conical reflectance factor (CCRF) has been calculated as an alternative to the bidirectional reflectance distribution function (BRDF) for three types of bare sea ice with varying surface roughness (σ= 0.1–10) and ice thicknesses (50–2000 cm) over an incident solar irradiance wavelength range of 300–1400 nm. The comprehensive study of the CCRF of sea ice presented here is paramount for interpreting sea ice measurements from satellite imagery and inter-calibrating space-borne sensors that derive albedo from multiple multi-angular measurements. The calculations performed by a radiative-transfer code (PlanarRad) show that the CCRF of sea ice is sensitive to realistic values of surface roughness. The results presented here show that surface roughness cannot be considered independently of sea ice thickness, solar zenith angle and wavelength. A typical CCRF of sea ice has a quasi-isotropic reflectance over the hemisphere, associated with a strong forward-scattering peak of photons. Surface roughness is crucial for the location, size and intensity of the forward-scattering peak. As the surface roughness increases, a spreading of the CCRF peak is observed. The hemisphere was split in to 216 quadrangular regions or quads. The peak remains specular for the smaller surface roughnesses (σ=0.001 to σ=0.01), whereas for larger surface roughness features (above σ=0.05), the peak spreads out over multiple quads with a lower intensity than for smaller roughness features, and the highest value is displaced further out on the solar principal plane. Different types of sea ice have a similar pattern with wavelength: the CCRF increases by 30 % from first-year sea ice to multi-year sea ice at 400 nm and up to 631 % at 1100 nm, 32 % from melting sea ice to multi-year sea ice at 400 nm and a maximum of 98 % at 900 nm, and 11 % from melting sea ice to first-year sea ice at 400 nm and up to 86 % at 800 nm. The CCRF calculations presented in this study form the first set of complete CCRF values as an approximation of the BRDF for bare sea ice with a wide range of configurations.

show abstract

Airborne measurements of directional reflectivity over the Arctic marginal sea ice zone

Cited by 6 publications

References 44 publications

MOSAiC-ACA and AFLUX - Arctic airborne campaigns characterizing the exit area of MOSAiC

MOSAiC-ACA and AFLUX - Arctic airborne campaigns characterizing the exit area of MOSAiC

Airborne observations of the surface cloud radiative effect during different seasons over sea ice and open ocean in the Fram Strait

The effects of surface roughness on the calculated, spectral, conical–conical reflectance factor as an alternative to the bidirectional reflectance distribution function of bare sea ice

Contact Info

Product

Resources

About