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

Area of Science:

• * Climate Science
• * Arctic Research
• * Remote Sensing

Background:

• * Global climate change presents significant societal and political challenges.
• * Current climate models inadequately represent rapid Arctic warming and sea ice decline.
• * Improved understanding of Arctic climate dynamics is crucial for accurate climate projections.

Purpose of the Study:

• * To provide datasets for enhancing the understanding of ongoing Arctic climate changes.
• * To analyze temporal and spatial variations of surface albedo in the Arctic.
• * To correlate surface types with albedo measurements for improved climate modeling.

Main Methods:

• * Conducted 29 helicopter flights (May-September 2020) during the MOSAiC expedition.
• * Utilized fisheye camera images to determine surface type distributions (ice, melt ponds, open water).
• * Employed multiple linear regression to link albedo data with surface types and irradiance measurements.

Main Results:

• * Quantified surface-type fractions and their impact on surface albedo.
• * Provided detailed albedo data and solar irradiance measurements across different Arctic surface types.
• * Documented changes in surface albedo throughout the melt and refreeze season.

Conclusions:

• * The provided datasets offer valuable insights into Arctic surface albedo dynamics.
• * This data can help refine climate models for better Arctic change predictions.
• * Enhanced understanding of surface-albedo interactions is key to addressing Arctic climate challenges.