Publication Abstracts

Alexandrov et al. 2018

Alexandrov, M.D., B. Cairns, K. Sinclair, A.P. Wasilewski, L. Ziemba, E. Crosbie, R. Moore, J. Hair, A.J. Scarino, Y. Hu, S. Stamnes, M.A. Shook, and G. Chen, 2018: Retrievals of cloud droplet size from the research scanning polarimeter data: Validation using in situ measurements. Remote Sens. Environ., 210, 76-95, doi:10.1016/j.rse.2018.03.005.

We present comparisons of cloud droplet size distributions (DSDs) retrieved from the research scanning polarimeter (RSP) data with correlative in situ measurements made during the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). The airborne portion of this field experiment was based out of St. John's airport, Newfoundland, Canada with the focus of this paper being on the deployment in May-June 2016. RSP was onboard the NASA C-130 aircraft together with an array of in situ and other remote sensing instrumentation. The RSP is an along-track scanner measuring the polarized and total reflectance in 9 spectral channels. Its uniquely high angular resolution allows for characterization of liquid water droplet sizes using the rainbow structure observed in the polarized reflectance over the scattering angle range from 135° to 165°. The rainbow is dominated by single scattering of light by cloud droplets, so its structure is characteristic specifically of the droplet sizes at cloud top (within unit optical depth into the cloud, equivalent to approximately 50 m). A parametric fitting algorithm applied to the polarized reflectance provides retrievals of the droplet effective radius and variance assuming a prescribed size distribution shape (gamma distribution). In addition to this, we use a non-parametric method, the Rainbow Fourier Transform (RFT), which allows us to retrieve the droplet size distribution itself. The latter is important in the case of clouds with complex microphysical structure, or multiple layers of cloud, which result in multi-modal DSDs. During NAAMES the aircraft performed a number of flight patterns specifically designed for comparisons between remote sensing retrievals and in situ measurements. These patterns consisted of two flight segments above the same straight ground track. One of these segments was flown above clouds allowing for remote sensing measurements, while the other was near the cloud top where cloud droplets were sampled. We compare the DSDs retrieved from the RSP data with in situ measurements made by the Cloud Droplet Probe (CDP). The comparisons generally show good agreement (better than 1 µm for effective radius and in most cases better than 0.02 for effective variance) with deviations explainable by the position of the aircraft within the cloud, or by the presence of additional cloud layers between the cloud being sampled by the in situ instrumentation and the altitude of the remote sensing segment. In the latter case, the multi-modal DSDs retrieved from the RSP data were consistent with the multi-layer cloud structures observed in the correlative High Spectral Resolution Lidar (HSRL) profiles. The results of these comparisons provide a rare validation of polarimetric droplet size retrieval techniques, demonstrating their accuracy and robustness and the potential of satellite data of this kind on a global scale.

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BibTeX Citation

  author={Alexandrov, M. D. and Cairns, B. and Sinclair, K. and Wasilewski, A. P. and Ziemba, L. and Crosbie, E. and Moore, R. and Hair, J. and Scarino, A. J. and Hu, Y. and Stamnes, S. and Shook, M. A. and Chen, G.},
  title={Retrievals of cloud droplet size from the research scanning polarimeter data: Validation using in situ measurements},
  journal={Remote Sens. Environ.},

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RIS Citation

ID  - al05600n
AU  - Alexandrov, M. D.
AU  - Cairns, B.
AU  - Sinclair, K.
AU  - Wasilewski, A. P.
AU  - Ziemba, L.
AU  - Crosbie, E.
AU  - Moore, R.
AU  - Hair, J.
AU  - Scarino, A. J.
AU  - Hu, Y.
AU  - Stamnes, S.
AU  - Shook, M. A.
AU  - Chen, G.
PY  - 2018
TI  - Retrievals of cloud droplet size from the research scanning polarimeter data: Validation using in situ measurements
JA  - Remote Sens. Environ.
VL  - 210
SP  - 76
EP  - 95
DO  - 10.1016/j.rse.2018.03.005
ER  -

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