Articles | Volume 10, issue 5
The Cryosphere, 10, 2379–2397, 2016
The Cryosphere, 10, 2379–2397, 2016

Research article 13 Oct 2016

Research article | 13 Oct 2016

Improving satellite-retrieved surface radiative fluxes in polar regions using a smart sampling approach

Kristof Van Tricht1,*, Stef Lhermitte1,2, Irina V. Gorodetskaya1,3, and Nicole P. M. van Lipzig1 Kristof Van Tricht et al.
  • 1KU Leuven – University of Leuven Department of Earth and Environmental Sciences, Celestijnenlaan 200E, 3001 Leuven, Belgium
  • 2Department of Geoscience & Remote Sensing, Delft University of Technology, Delft, the Netherlands
  • 3CESAM – Centre for Environmental and Marine Studies, Department of Physics, University of Aveiro, Campus Universitario de Santiago, 3810-193 Aveiro, Portugal
  • * Invited contribution by K. Van Tricht, recipient of the EGU Outstanding Student Poster (OSP) Award 2015.

Abstract. The surface energy budget (SEB) of polar regions is key to understanding the polar amplification of global climate change and its worldwide consequences. However, despite a growing network of ground-based automatic weather stations that measure the radiative components of the SEB, extensive areas remain where no ground-based observations are available. Satellite remote sensing has emerged as a potential solution to retrieve components of the SEB over remote areas, with radar and lidar aboard the CloudSat and CALIPSO satellites among the first to enable estimates of surface radiative long-wave (LW) and short-wave (SW) fluxes based on active cloud observations. However, due to the small swath footprints, combined with a return cycle of 16 days, questions arise as to how CloudSat and CALIPSO observations should be optimally sampled in order to retrieve representative fluxes for a given location. Here we present a smart sampling approach to retrieve downwelling surface radiative fluxes from CloudSat and CALIPSO observations for any given land-based point-of-interest (POI) in polar regions. The method comprises a spatial correction that allows the distance between the satellite footprint and the POI to be increased in order to raise the satellite sampling frequency. Sampling frequency is enhanced on average from only two unique satellite overpasses each month for limited-distance sampling < 10 km from the POI, to 35 satellite overpasses for the smart sampling approach. This reduces the root-mean-square errors on monthly mean flux estimates compared to ground-based measurements from 23 to 10 W m−2 (LW) and from 43 to 14 W m−2 (SW). The added value of the smart sampling approach is shown to be largest on finer temporal resolutions, where limited-distance sampling suffers from severely limited sampling frequencies. Finally, the methodology is illustrated for Pine Island Glacier (Antarctica) and the Greenland northern interior. Although few ground-based observations are available for these remote areas, important climatic changes have been recently reported. Using the smart sampling approach, 5-day moving average time series of downwelling LW and SW fluxes are demonstrated. We conclude that the smart sampling approach may help to reduce the observational gaps that remain in polar regions to further refine the quantification of the polar SEB.

Short summary
Despite the crucial role of polar regions in the global climate system, the limited availability of observations on the ground hampers a detailed understanding of their energy budget. Here we develop a method to use satellites to fill these observational gaps. We show that by sampling satellite observations in a smart way, coverage is greatly enhanced. We conclude that this method might help improve our understanding of the polar energy budget, and ultimately its effects on the global climate.