No abstract

SKYNET and Aerosol Robotic Network (AERONET) retrieved aerosol single scattering albedo (SSA) values of four sites, Chiba (Japan), Pune (India), Valencia (Spain), and Seoul (Korea), were compared to understand the factors behind often noted large SSA differences between them. SKYNET and AERONET algorithms are found to produce nearly same SSAs for similarity in input data, suggesting that SSA differences between them are primarily due to quality of input data due to different calibration and/or observation protocols as well as difference in quality assurance criteria. The most plausible reason for high SSAs in SKYNET is found to be underestimated calibration constant for sky radiance (ΔΩ). The disk scan method (scan area: 1° × 1° area of solar disk) of SKYNET is noted to produce stable wavelength‐dependent ΔΩ values in comparison to those determined from the integrating sphere used by AERONET to calibrate sky radiance. Aerosol optical thickness (AOT) difference between them can be the next important factor for their SSA difference, if AOTs between them are not consistent. Inconsistent values of surface albedo while analyzing data of SKYNET and AERONET can also bring SSA difference between them, but the effect of surface albedo is secondary. The aerosol nonsphericity effect is found to be less important for SSA difference between these two networks.

Polarized emissivities of the sea ice over the Arctic were retrieved at Advanced Microwave Scanning Radiometer–EOS 10.65, 18.7, 23.8, and 36.5 GHz channel frequencies. Results indicate that retrieved emissivities are consistent with other emissivity estimates. However, errors in the retrieved emissivity for multiyear sea ice at 23.8 and 36.5 GHz can be large up to 8% and 20%, respectively, because of ignoring the freeboard ice scattering and the use of the same emission layer as in 6.925 GHz. It is shown that the emissivity slope for first‐year ice between 10.65 and 18.7 GHz is opposite to that for multiyear sea ice, enabling a distinction between first‐year ice and multiyear ice. Using these differences in spectral features with ice types, an emissivity difference (vertically polarized emissivity difference between 10.65 and 18.7 GHz) was devised to differentiate between first‐year sea ice and multiyear sea ice. A comparison with the ice status information obtained from Cold Regions Research and Engineering Laboratory buoy measurements demonstrates that the method can separate first‐year ice from multiyear ice, implying that this technique enables us to obtain instantaneous and pixel‐level ice‐type information from space‐based passive microwave measurements.

Biological control agents including microbes and their products have been studied as sustainable crop protection strategies. Although aquatic microalgae have been recently introduced as a biological control agent, the underlying molecular mechanisms are largely unknown. The aim of the present study was to investigate the molecular mechanisms underlying biological control by microalga Chlorella fusca. Foliar application of C. fusca elicits induced resistance in Arabidopsis thaliana against Pseudomonas syringae pv. tomato DC3000 that activates plant immunity rather than direct antagonism. To understand the basis of C. fuscatriggered induced resistance at the transcriptional level, we conducted RNA sequencing (RNA-seq) analysis. RNA-seq data showed that, upon pathogen inoculation, C. fusca treatment primed the expression of cysteine-rich receptor-like kinases, WRKY transcription factor genes, and salicylic acid and jasmonic acid signalling-related genes. Intriguingly, the application of C. fusca primed pathogen-associated molecular pattern -triggered immunity, characterized by reactive oxygen species burst and callose deposition, upon flagellin 22 treatment. The attempts to find C. fusca determinants allowed us to identify D-lactic acid secreted in the supernatant of C. fusca as a defence priming agent. This is the first report of the mechanism of innate immune activation by aquatic microalga Chlorella in higher plants.