A better understanding of POLDER's cloud droplet size retrieval: impact of cloud horizontal inhomogeneity and directional sampling

Abstract

Abstract. The principles of the Polarization and Directionality of the Earth's Reflectance (POLDER) cloud droplet size retrieval requires that clouds are horizontally homogeneous. Nevertheless, the retrieval is applied by combining all measurements from an area of 150 km × 150 km to compensate for POLDER's insufficient directional sampling. Using the POLDER-like data simulated with the RT3 model, we investigate the impact of cloud horizontal inhomogeneity and directional sampling on the retrieval, and then analyze which spatial resolution is potentially accessible from the measurements. Case studies show that the sub-scale variability in droplet effective radius (CDR) can mislead both the CDR and effective variance (EV) retrievals. Nevertheless, the sub-scale variations in EV and cloud optical thickness (COT) only influence the EV retrievals and not the CDR estimate. In the directional sampling cases studied, the retrieval is accurate using limited observations and is largely independent of random noise. Several improvements have been made to the original POLDER droplet size retrieval. For example, the measurements in the primary rainbow region (137–145°) are used to ensure accurate large droplet (> 15 μm) retrievals and reduce the uncertainties caused by cloud heterogeneity. We apply the improved method using the POLDER global L1B data for June 2008, the new CDR results are compared with the operational CDRs. The comparison show that the operational CDRs tend to be underestimated for large droplets. The reason is that the cloudbow oscillations in the scattering angle region of 145–165° are weak for cloud fields with CDR > 15 μm. Lastly, a sub-scale retrieval case is analyzed, illustrating that a higher resolution, e.g., 42 km × 42 km, can be used when inverting cloud droplet size parameters from POLDER measurements.

Comparisons of bispectral and polarimetric cloud microphysical retrievals using LES-Satellite retrieval simulator

“…We found that the differences between the two techniques are negligible (Δr e~0 .01 µm and Δv e~0 .001) and do not significantly vary with final resolution. Apparently, the importance of the aggregation rules in the LES are far less important than what we 25 had found in the multiple-moment cases tested in Shang, et al (2015). One clear difference between the these multiple moment cases and the LES was that the toy models are reductive bimodal distributions, exhibiting very large sub-scale microphysical inhomogeneity in r e that is not commonly observed in the LES or in observational studies.…”

“…Cloudy pixels is defined using a threshold of τ LES >0.1. Shang et al (2015). There results are replicated here and compared to the arithmetic mean r e (<r e >), and the mathematical aggregation results (r e ' and v e ') defined in eq.…”

“…The differences between the two methods are discussed in the Appendix. The main conclusion is that, although the two aggregation methods could be different in some hypothetical cases that have unrealistically large small-scale variation of DSD (Shang et al 2015), they are essentially equivalent for practical purposes. In this study, we simply aggregate r e (2WT) and v e (2WT) from the native LES resolution of 50 m to 5…”

“…The microphysical aggregation rules allow for the explanation of some features of the coarse polarimetric retrieval experiments displayed in Shang et al (2015). Referring to the inhomogeneous polarimetric retrieval experiments in table 2 5 and figure 4 of their paper, we reproduced their results and calculated the corresponding r e ' and v e ' in our Table 2, which contains the same retrieval examples and corresponding r e ' and v e ' results for the cases examined in their study.…”