Gridded Melt Pond Cover Fraction on Arctic Sea Ice derived from TERRA-MODIS 8-day composite Reflectance Data

• Main Authors: Rösel, Anja, Kaleschke, Lars, Kern, Stefan
• Format: Dataset
• Language: English
• Published: World Data Center for Climate (WDCC) at DKRZ 2013
• Subjects: Climate; CliSAP; arctic; ocean; Arctic; Arctic Ocean; Climate change; Sea ice
• Online Access: https://dx.doi.org/10.1594/wdcc/modis__arctic__mpf; http://cera-www.dkrz.de/WDCC/ui/Compact.jsp?acronym=MODIS__Arctic__MPF

Project: Integrated Climate System Analysis and Prediction - Within CliSAP (Integrated Climate System Analysis and Prediction) the ongoing and past changes of state of the climate system are analysed, in response to natural and anthropogenic perturbations. The goal set is the determination of predictable elements of the climate system over a broad range of space and time scales as well as of uncertainties intrinsic to predictions of important climate system and environmental indices. In terms of regional consequences of climate change, potential impacts of such changes on humans are quantified, including economy, security and their environment, with a focus on Northern Europe. CliSAP is the Cluster of Excellence at the University of Hamburg funded by the DFG (Deutsche Forschungsgesellschaft) and under the participation of the Max Planck Institute for Meteorology, the Institute for Coastal Research of the GKSS Research Centre, and the German Climate Computing Centre (DKRZ): http://www.clisap.de/ , https://www.klimacampus-hamburg.de . Summary: Reflectances measured in the visible frequency range at three channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Earth Observation Satellite (EOS) TERRA were used to derive the melt pond fraction on Arctic sea ice using an artificial neural network. This analysis was done on reflectances gridded onto a polar-stereographic grid tangent to the Earths' surface at 70 deg N with 500 m grid resolution. The reflectances used originate from the 8-day composite reflectances provided via https://wist.echo.nasa.gov/api/ as product: "MODIS surface Reflectance 8-Day L3 Global 500m SIN Grid V005". After gridding and flagging for clouds and other disturbances the artificial neural network was applied, providing fractions of three surface classes: 1) melt ponds, 2) sea ice and snow, and 3) open water at 500 m grid resolution. This data has been interpolated onto a similar polar-stereographic grid but with 12.5 km grid resolution. The data set offered here comprises several data layers: the melt pond fraction, its standard deviation, the open water fraction, and the number of individual valid grid cells with 500 m grid resolution included in each 12.5 km grid cell. In addition, in three separate data layers melt pond fraction, its standard deviation, and the open water fraction are given only for those grid cells (with 12.5 km grid resolution) where more than 90 % of the native 500 m grid resolution data indicate clear sky conditions. Grid cells with an open water fraction larger than 85 % have been generally flagged as invalid. The data set is updated annually.