Radiative closure and cloud effects on the radiation budget based on satellite and shipborne observations during the Arctic summer research cruise, PS106

Velasco, Carola Barrientos; Deneke, Hartwig; Hünerbein, Anja; Griesche, Hannes; Seifert, Patric; Macke, Andreas

doi:10.5194/acp-22-9313-2022

Cited by 14 publications

(14 citation statements)

References 109 publications

(144 reference statements)

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“… andBarrientos-Velasco et al (2022).The presented findings demonstrate that a detailed characterization of the low-level clouds can significantly improve the quality of radiative transfer simulations. In the standard configuration of processing schemes for cloud microphysical products, such as Cloudnet, these low-level clouds are often underrepresented.…”

mentioning

confidence: 59%

“…Here, the cloud properties derived by Cloudnet, based on the remote-sensing observations were applied. The method implemented in this analysis first compares the simulated radiative fluxes with observed values of downward solar (SD) and terrestrial radiative fluxes (TD) and then derives the CRE at the surface, following Barrientos-Velasco et al (2022). The current study defines the CRE as the difference between an all-sky and a clear-sky atmosphere.…”

Section: T-cars Simulationsmentioning

confidence: 99%

“…We propose a method to reduce downward radiative flux biases of low-level stratus clouds (LLS) by evaluating the flux differences between 1-D radiative transfer simulations and observations collected during the PS106 cruise. The simulations were performed with the TROPOS (Leibniz Institute of Tropospheric Research) Cloud and Aerosol Radiative effect Simulator (T-CARS) (Barlakas et al, 2020;Witthuhn et al, 2021;Barrientos-Velasco et al, 2022). Cloud properties derived by the instrument synergy approach Cloudnet (Illingworth et al, 2007;Tukiainen et al, 2020) served as realistic input parameters for the radiative transfer simulations and the surface radiation measurements of the OCEANET-Atmosphere facility (hereafter referred to as OCEANET) as true validation data.…”

Section: Introductionmentioning

confidence: 99%

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Low-level Arctic clouds: A blind zone in our knowledge of the radiation budget

Griesche

Velasco

Deneke

et al. 2023

Preprint

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Abstract. Quantifying the role of clouds in the Earth radiation budget is essential for improving our understanding of the drivers and feedbacks of climate change. This holds in particular for the Arctic, the region currently undergoing the most rapid changes. This region, however, also poses significant challenges to remote-sensing retrievals of clouds and radiative fluxes, introducing large uncertainties in current climate data records. In particular, low-level stratiform clouds are common in the Arctic but are, due to their low altitude, challenging to observe and characterize with remote-sensing techniques. The availability of reliable ground-based observations as reference is thus of high importance. In the present study, radiative transfer simulations based on state-of-the-art ground-based remote sensing of clouds are contrasted to surface radiative flux measurements to assess their ability to constrain the cloud radiative effect. Cloud radar, lidar, and microwave radiometer observations from the PS106 cruise in the Arctic marginal sea ice zone in summer 2017 were used to derive cloud micro- and macrophysical properties by means of the instrument synergy approach of Cloudnet. Closure of surface radiative fluxes can only be achieved by a realistic representation of the low-level liquid-containing clouds in the radiative transfer simulations. The original, likely erroneous, representation of these low-level clouds in the radiative transfer simulations let to errors in the cloud radiative effect of 43 W m-2. The present study highlights the importance of jointly improving retrievals for low-level liquid-containing clouds which are frequently encountered in the high Arctic, together with observational capabilities both in terms of cloud remote sensing and radiative flux observations. Concrete suggestions for achieving these goals are provided.

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mentioning

confidence: 59%

Section: T-cars Simulationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Low-level Arctic clouds: A blind zone in our knowledge of the radiation budget

Griesche

Velasco

Deneke

et al. 2023

Preprint

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“…However, measurements of the REB and the CRE are difficult to obtain over open ocean. Shipborne radiation measurements mostly consist of the downward irradiances only and rely on assumptions or complementary (e. g., satellite) measurements of surface albedo, near-surface air temperature, and surface emissivity to calculate the upward irradiances (Protat et al, 2017;Barrientos-Velasco et al, 2022). Polavarapu (1978) obtained the net irradiance from a combination of two pairs of radiometers, which were mounted at the left and right outsides of the ship's structure and shadowed at the half facing towards the ship.…”

Section: Introductionmentioning

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

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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.

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“…Accurate retrievals of cloud thermodynamic phase are required for constraining cloud phase representation in GCM (Fiddes et al, 2022). Several studies showed that the shortwave radiative transfer, especially through mixed-phase clouds, depends highly on the amount and location of liquid cloud droplets (McFarquhar et al, 2021;Barrientos-Velasco et al, 2022). An underestimation in the liquid water-path (LWP) leads to a less radiative opaque cloud, which subsequently leads to an underestimation of the cloud radiative effect at the surface (Cesana & Storelvmo, 2017;Tan & Storelvmo, 2019).…”

Section: Introductionmentioning

confidence: 99%

Improved cloud phase retrievals based on remote-sensing observations have the potential to decrease the Southern Ocean shortwave cloud radiation bias

Schimmel

Velasco

Witthuhn³

et al. 2023

Preprint

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Accurately identifying liquid water layers in mixed-phase clouds is crucial for estimating cloud radiative effects. Lidar-based retrievals are limited in optically thick or multilayer clouds, leading to positive biases in simulated shortwave radiative fluxes. At the same time, general circulation models also tend to overestimate the downwelling shortwave radiation at the surface especially in the Southern Ocean regions. To reduce this SW radiation bias in models, we first need better observational-based retrievals for liquid detection which can later be used for model validation. To address this, a machine-learning-based liquid-layer detection method called VOODOO was employed in a proof-of-concept study using a single column radiative transfer model to compare shortwave cloud radiative effects of liquid-containing clouds detected by Cloudnet and VOODOO to ground-based and satellite observations. Results showed a reduction in shortwave radiation bias, indicating that liquid-layer detection with machine-learning retrievals can improve radiative transfer simulations.

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Radiative closure and cloud effects on the radiation budget based on satellite and shipborne observations during the Arctic summer research cruise, PS106

Cited by 14 publications

References 109 publications

Low-level Arctic clouds: A blind zone in our knowledge of the radiation budget

Low-level Arctic clouds: A blind zone in our knowledge of the radiation budget

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

Improved cloud phase retrievals based on remote-sensing observations have the potential to decrease the Southern Ocean shortwave cloud radiation bias

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