18 research outputs found

    Seasonality of spectral radiative fluxes and optical properties of Arctic sea ice during the spring–summer transition

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    The reflection, absorption, and transmittance of shortwave solar radiation by sea ice play crucial roles in physical and biological processes in the ice-covered Arctic Ocean and atmosphere. These sea-ice optical properties, particularly during the melt season, significantly impact energy fluxes within and the total energy budget of the coupled atmosphere-ice-ocean system. We analyzed data from autonomous drifting stations to investigate the seasonal evolution of the spectral albedo, transmittance, and absorptivity for different sea-ice, snow, and surface conditions measured during the MOSAiC expedition in 2019–2020. The spatial variability of these properties was small during spring and increased strongly after melt onset on May 26, 2020, when liquid water content on the surface increased, largely accounting for the enhanced variability. The temporal evolution of surface albedo and sea-ice transmittance was mostly event-driven, thus containing episodic elements. Melt ponds reduced the local surface albedo by 31%–45%. Over the melting season, single ponding events increased the energy deposition of the sea ice by 35% compared to adjacent bare ice. Thus, single melt ponds may impact the summer energy budget as much as seasonal evolution over 1 month. Absorptivity and transmittance showed strong temporal and spatial variabilities independently of surface conditions, possibly due to the different internal sea-ice properties and under-ice biological processes. The differences in seasonal evolution shown for different sea-ice conditions strongly impacted the partitioning of shortwave solar radiation.This study shows that the formation and development of melt ponds, in reducing albedo by a third of bare ice sites, can notably increase the total summer heat deposition.The vastly different seasonal evolutions, different sea-ice conditions, and timing and duration of ponding events need to be considered when comparing local in-situ observations with large-scale satellite remote sensing datasets, which we suggest can help to improve numerical models

    Sea Ice Melt Pond Fraction Derived From Sentinel‐2 Data: Along the MOSAiC Drift and Arctic‐Wide

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    Melt ponds forming on Arctic sea ice in summer significantly reduce the surface albedo and impact the heat and mass balance of the sea ice. Therefore, their areal coverage, which can undergo rapid change, is crucial to monitor. We present a revised method to extract melt pond fraction (MPF) from Sentinel-2 satellite imagery, which is evaluated by MPF products from higher-resolution satellite and helicopter-borne imagery. The analysis of melt pond evolution during the MOSAiC campaign in summer 2020, shows a split of the Central Observatory (CO) into a level ice and a highly deformed ice part, the latter of which exhibits exceptional early melt pond formation compared to the vicinity. Average CO MPFs are 17% before and 23% after the major drainage. Arctic-wide analysis of MPF for years 2017–2021 shows a consistent seasonal cycle in all regions and years

    Optimization of Carbon Ion Treatment Plans by Integrating Tissue Specific α/β-Values for Patients with Non-Resectable Pancreatic Cancer.

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    The aim of the thesis is to improve treatment plans of carbon ion irradiation by integrating the tissues' specific [Formula: see text]-values for patients with locally advanced pancreatic cancer (LAPC).Five patients with LAPC were included in this study. By the use of the treatment planning system Syngo RT Planning (Siemens, Erlangen, Germany) treatment plans with carbon ion beams have been created. Dose calculation was based on [Formula: see text]-values for both organs at risk (OAR) and the tumor. Twenty-five treatment plans and thirty-five forward calculations were created. With reference to the anatomy five field configurations were included. Single Beam Optimization (SBO) and Intensity Modulated Particle Therapy (IMPT) were used for optimization. The plans were analyzed with respect to both dose distributions and individual anatomy. The plans were evaluated using a customized index.With regard to the target, a field setup with one single posterior field achieves the highest score in our index. Field setups made up of three fields achieve good results in OAR sparing. Nevertheless, the field setup with one field is superior in complex topographic conditions. But, allocating an [Formula: see text]-value of 2 Gy to the spinal cord leads to critical high maximum doses in the spinal cord. The evaluation of dose profiles showed significant dose peaks at borders of the [Formula: see text]-gradient, especially in case of a single posterior field.Optimization with specific [Formula: see text]-values allows a more accurate view on dose distribution than previously. A field setup with one single posterior field achieves good results in case of difficult topographic conditions, but leads to high maximum doses to the spinal cord. So, field setups with multiple fields seem to be more adequate in case of LAPC, being surrounded by highly radiosensitive normal tissues

    Surface albedo measurements and surface type classification from helicopter-based observations during MOSAiC

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    Abstract Global climate change poses significant societal and political challenges. The rapid increase in the near-surface air temperatures and the drastic retreat of the Arctic sea ice during summer are not well represented by climate models. The data sets introduced here intend to help improving the current understanding of the ongoing Arctic climate changes. In particular, this study considers observations from 24 helicopter flights (June–September 2020) and 5 flights with the helicopter-towed probe HELiPOD (May–July 2020) during MOSAiC. Distributions of various surface types (white ice/snow, bright melt ponds, dark melt ponds, open water, and bare ice) were determined using fisheye camera images. They were related to collocated broadband irradiance measurements to analyse the temporal and spatial changes of the surface albedo. Multiple linear regression was applied to assign the measured areal albedo to the corresponding surface-types. The resulting surface-type fractions, the albedo data and respective upward and downward broadband solar irradiances of several flights throughout the melting and refreezing season are provided

    Observations and modeling of areal surface albedo and surface types in the Arctic

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    An accurate representation of the annual evolution of surface albedo of the Arctic Ocean, especially during the melting period, is crucial to obtain reliable climate model predictions in the Arctic. Therefore, the output of the surface albedo scheme of a coupled regional climate model (HIRHAM–NAOSIM) was evaluated against airborne and ground-based measurements. The observations were conducted during five aircraft campaigns in the European Arctic at different times of the year between 2017 and 2022; one of them was part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in 2020. We applied two approaches for the evaluation: (a) relying on measured input parameters of surface type fraction and surface skin temperature (offline) and (b) using HIRHAM–NAOSIM simulations independently of observational data (online). From the offline method we found a seasonally dependent bias between measured and modeled surface albedo. In spring, the cloud effect on surface broadband albedo was overestimated by the surface albedo parametrization (mean albedo bias of 0.06), while the surface albedo scheme for cloudless cases reproduced the measured surface albedo distributions for all seasons. The online evaluation revealed an overestimation of the modeled surface albedo resulting from an overestimation of the modeled cloud cover. Furthermore, it was shown that the surface type parametrization contributes significantly to the bias in albedo, especially in summer (after the drainage of melt ponds) and autumn (onset of refreezing). The lack of an adequate model representation of the surface scattering layer, which usually forms on bare ice in summer, contributed to the underestimation of surface albedo during that period. The difference between modeled and measured net irradiances for selected flights during the five airborne campaigns was derived to estimate the impact of the model bias for the solar radiative energy budget at the surface. We revealed a negative bias between modeled and measured net irradiances (median: −6.4 W m−2) for optically thin clouds, while the median value of only 0.1 W m−2 was determined for optically thicker clouds
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