Articles | Volume 9, issue 8
Atmos. Meas. Tech., 9, 3641–3659, 2016
Atmos. Meas. Tech., 9, 3641–3659, 2016

Research article 09 Aug 2016

Research article | 09 Aug 2016

Toward autonomous surface-based infrared remote sensing of polar clouds: cloud-height retrievals

Penny M. Rowe1,2, Christopher J. Cox3,4, and Von P. Walden5 Penny M. Rowe et al.
  • 1NorthWest Research Associates, Redmond, WA, USA
  • 2Physics Department, Universidad de Santiago de Chile, Santiago, Chile
  • 3Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA
  • 4NOAA Earth System Research Laboratory, Physical Sciences Division, Boulder, CO, USA
  • 5Department of Civil and Environmental Engineering, Washington State University, Pullman, WA, USA

Abstract. Polar regions are characterized by their remoteness, making measurements challenging, but an improved knowledge of clouds and radiation is necessary to understand polar climate change. Infrared radiance spectrometers can operate continuously from the surface and have low power requirements relative to active sensors. Here we explore the feasibility of retrieving cloud height with an infrared spectrometer that would be designed for use in remote polar locations. Using a wide variety of simulated spectra of mixed-phase polar clouds at varying instrument resolutions, retrieval accuracy is explored using the CO2 slicing/sorting and the minimum local emissivity variance (MLEV) methods. In the absence of imposed errors and for clouds with optical depths greater than  ∼  0.3, cloud-height retrievals from simulated spectra using CO2 slicing/sorting and MLEV are found to have roughly equivalent high accuracies: at an instrument resolution of 0.5 cm−1, mean biases are found to be  ∼  0.2 km for clouds with bases below 2 and −0.2 km for higher clouds. Accuracy is found to decrease with coarsening resolution and become worse overall for MLEV than for CO2 slicing/sorting; however, the two methods have differing sensitivity to different sources of error, suggesting an approach that combines them. For expected errors in the atmospheric state as well as both instrument noise and bias of 0.2 mW/(m2 sr cm−1), at a resolution of 4 cm−1, average retrieval errors are found to be less than  ∼  0.5 km for cloud bases within 1 km of the surface, increasing to  ∼  1.5 km at 4 km. This sensitivity indicates that a portable, surface-based infrared radiance spectrometer could provide an important complement in remote locations to satellite-based measurements, for which retrievals of low-level cloud are challenging.

Short summary
Clouds play an important role in the rapid climate change occurring in polar regions, yet cloud measurements are challenging in such harsh, remote environments. Here we explore how well a proposed low-power infrared spectrometer, which would be highly portable, could be used to determine cloud height. Using simulated data, we estimate retrieval accuracy, finding that such an instrument would be able to constrain cloud height, particular for low, thick clouds, which are common in polar region.