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The supramolecular self-assembly of para-substituted tetraphenylporphyrin complexes of zinc(II), Zn(p-X)TPP, with imidazolyl-linked porphyrinatomanganese(III), Mn(p-lmBPTPP)Cl, driven by coordinative bonding has been investigated by fluorescence spectra, electrospray mass spectrometry, 1 H-n.m.r. and u.v.-vis. spectra. The association constants of the supramolecular complexes, K c , were calculated using fluorescence spectroscopic titration data at suitable dilute concentration ranges in which the fluorescent quenching of Zn(p-X)TPP by Mn(p-ImBPTPP)Cl is a static process. The electronic effect in the supramolecular self-assembly of para-substituted . porphyrinatozinc(II) with imidazolyl-linked porphyrinatomanganese(III) is discussed. The non-linear dependence of log K c on the Hammett constants was found, which suggested that the electronic effect in para-substituents of tetraphenylporphyrin complexes of zinc(II) is an important, but not a sole factor effecting the association constants of the Zn(p-X)TPP-Mn(p-ImBPTPP)Cl supramolecular complexes. The results indicate that the closed conformation of the Zn(p-X)TPP-Mn(p-ImBPTPP)Cl supramolecular complex is another important factor effecting the association constants of the Zn(p-X)TPP-Mn(p-ImBPTPP)Cl supramolecular complexes.

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Understanding moisture information ahead of tropical cyclone (TC) convection is very important for predicting TC track, intensity, and precipitation. The advanced Himawari imager onboard the Japanese Himawari‐8/‐9 satellite can provide high spatial and temporal resolution moisture information. Three‐layered precipitable water (LPW) with its three water vapor absorption infrared bands can be assimilated to generate better understanding and prediction of TC evolution. The impacts of LPW assimilation in the Weather Research and Forecasting model with nine combinations of physical parameterization schemes, including three cumulus parameterization (CP) and three microphysics parameterization (MP) schemes on TC prediction, have been comprehensively analyzed using Typhoon Hato as a case study. The results indicate that LPW assimilation reduces the average track error and speed up TC movement by better adjustment of the atmospheric circulation fields via changing the vertical structure of moisture and thermal profile. The track forecasts retain sensitivity to CP schemes after LPW assimilation. Also, LPW assimilation improves TC intensity prediction because the latent heat release process is accurately adjusted. It has been revealed that LPW assimilation can weaken the intensity sensitivity to MP schemes more than to CP schemes. Skill scores were used to evaluate precipitation forecasts after Hato's landfall. The results indicate that heavy precipitation forecasts are more sensitive to the choice of MP schemes. After LPW assimilation, the equitable threat scores among different results become similar and all forecast skills are increased. In addition, group statistic results with different initial time show the same conclusions.