Development of a new data-processing method for SKYNET sky radiometer observations

Abstract

Abstract. In order to reduce uncertainty in the estimation of Direct Aerosol Radiative Forcing (DARF), it is important to improve the estimation of the single scattering albedo (SSA). In this study, we propose a new data processing method to improve SSA retrievals for the SKYNET sky radiometer network, which is one of the growing number of networks of sun-sky photometers, such as NASA AERONET and others. There are several reports that SSA values from SKYNET have a bias compared to those from AERONET, which is regarded to be the most accurate due to its rigorous calibration routines and data quality and cloud screening algorithms. We investigated possible causes of errors in SSA that might explain the known biases through sensitivity experiments using a numerical model, and also using real data at the SKYNET sites at Pune (18.616 • N/73.800 • E) in India and Beijing (39.586 • N/116.229 • E) in China. Sensitivity experiments showed that an uncertainty of the order of ±0.03 in the SSA value can be caused by a possible error in the ground surface albedo or solid view angle assumed for each observation site. Another candidate for possible error in the SSA was found in cirrus contamination generated by imperfect cloud screening in the SKYNET data processing. Therefore, we developed a new data quality control method to get rid of low quality or cloud contamination data, and we applied this method to the real observation data at the Pune site in SKYNET. After applying this method to the observation data, we were able to screen out a large amount of cirruscontaminated data and to reduce the deviation in the SSA value from that of AERONET. We then estimated DARF using data screened by our new method. The result showed that the method significantly reduced the difference of 5 W m −2 that existed between the SKYNET and AERONET values of DARF before screening. The present study also suggests the necessity of preparing suitable a priori information on the distribution of coarse particles ranging in radius between 10 µm and 30 µm for the analysis of heavily dust-laden atmospheric cases.

Overview of the Chemistry-Aerosol Mediterranean Experiment/Aerosol Direct Radiative Forcing on the Mediterranean Climate (ChArMEx/ADRIMED) summer 2013 campaign

“…4), but showed a quite similar extended particle size range with larger concentrations in almost all channels except the extremes (not shown). The four other drifting balloons launched in the dust layer during this event on 17 and 19 June (Table 5) did confirm the presence of very large particles (> 20 µm), which cannot be reported by the AERONET particle size distribution retrieval algorithm (Hashimoto et al, 2012). In addition, observations of large particles (> 15 µm) were systematically found during all other LOAC balloon flights drifting in African dust layers, which will need further analysis to better understand the process that can maintain such large particles in suspension during several days.…”

In situ measurements of desert dust particles above the western Mediterranean Sea with the balloon-borne Light Optical Aerosol Counter/sizer (LOAC) during the ChArMEx campaign of summer 2013

“…The small-radius discrepancies could be due to local variability in the dust content, like on the 27 June when AERONET retrieves a concentration increase centred on 0.25 µm in radius, and to respective uncertainties of both methods. On the other end of the particle size range, AERONET retrieval is not very sensitive to the particles larger than 7 µm in radius and the largest size class considered in the algorithm (15 µm in radius) is limited to particles smaller than about 19.7 µm in radius (Dubovik and King, 2000;Hashimoto et al, 2012). Thus, LOAC could have detected large particles that were not retrievable from AERONET observations.…”

Estimation of aerosol complex refractive indices for both fine and coarse modes simultaneously based on AERONET remote sensing products

“…There are several long-term Sun-sky-radiometer networks operated regionally or globally, e.g., AERONET (Holben et al, 1998(Holben et al, , 2001) and SKYNET (Hashimoto et al, 2012). Several inversion algorithms (e.g., King et al, 1978;Nakajima et al, 1996;King, 2000, 2006;Li et al, 2006) have been developed based on Sun-sky radiometers to retrieve aerosol parameters, like aerosol optical depth (τ ), single-scattering albedo, absorbing aerosol optical depth (τ a , AAOD), volume particle size distribution (VPSD), and the real (n(λ)) and imaginary (k(λ)) parts of CRIs corresponding to total-column atmospheric aerosols.…”

“…Calculating the effective CRI corresponding to each VPSD bin. Here, based on the guessed CRIs of both fine and coarse modes in the previous step, we employ an internal mixing approach, following the volume average rule (Heller, 1965), to estimate the CRI of each particle radius bin:…”