Improvement of X-Band Polarization Radar Melting Layer Recognition by the Bayesian Method and ITS Impact on Hydrometeor Classification

Using melting layer(ML)and non-melting layer(NML)data observed with the X-band dual linear polarization Doppler weather radar(X-POL)in Shunyi,Beijing,the reflectivity(ZH),differential reflectivity(ZDR),and correlation coefficient(CC)in the ML and NML are obtained in several stable precipitation processes.The prior probability density distributions(PDDs)of the ZH,ZDR and CC are calculated first,and then the probabilities of ZH,ZDR and CC at each radar gate are determined(PBB in the ML and PNB in the NML)by the Bayesian method.When PBB>PNB the gate belongs to the ML,and when PBB<PNB the gate belongs to the NML.The ML identification results with the Bayesian method are contrasUsing melting layer(ML)and non-melting layer(NML)data observed with the X-band dual linear polarization Doppler weather radar(X-POL)in Shunyi,Beijing,the reflectivity(ZH),differential reflectivity(ZDR),and correlation coefficient(CC)in the ML and NML are obtained in several stable precipitation processes.The prior probability density distributions(PDDs)of the ZH,ZDR and CC are calculated first,and then the probabilities of ZH,ZDR and CC at each radar gate are determined(PBB in the ML and PNB in the NML)by the Bayesian method.When PBB>PNB the gate belongs to the ML,and when PBB<PNB the gate belongs to the NML.The ML identification results with the Bayesian method are contrasted under the conditions of the independent PDDs and joint PDDs of the ZH,ZDR and CC.The results suggest that MLs can be identified effectively,although there are slight differences between the two methods.Because the values of the polarization parameters are similar in light rain and dry snow,it is difficult for the polarization radar to distinguish them.After using the Bayesian method to identify the ML,light rain and dry snow can be effectively separated with the X-POL observed data.ted under the conditions of the independent PDDs and joint PDDs of the ZH,ZDR and CC.The results suggest that MLs can be identified effectively,although there are slight differences between the two methods.Because the values of the polarization parameters are similar in light rain and dry snow,it is difficult for the polarization radar to distinguish them.After using the Bayesian method to identify the ML,light rain and dry snow can be effectively separated with the X-POL observed data.

Distribution of functional microorganisms and its significance for iron, sulphur, and nitrogen cycles in reservoir sediments

The biogeochemical cycles of sulphur(S),iron(Fe)and nitrogen(N)elements play a key role in the reservoir ecosystem.However,the spatial positioning and interrelationship of S,Fe and N cycles in the reservoir sediment profile have not been explored to a greater extent.Here,we measure the gradients of Fe^(2+),SO_(4)^(2-),NO_(3)^(-),NH_(4)^(+),DOC,TC and TN in the pore water of the sediment,and combining the vertical distribution of the functional microorganisms involved in S,Fe and N cyclings in the sediments to determine the redox stratification in the sediment.It is found that the geochemical gradient of S,Fe and N of the reservoir sedimentary column is mainly defined by the redox process involved in the related functional microorganisms.According to the type of electron acceptor,the sediment profile is divided into 3 redox intervals,namely aerobic respiration(0–10 cm),denitrification/iron reduction(10–28 cm)and sulfate reduction(28–32 cm).In the aerobic respiration zone,NH_(4)^(+)is oxidized by aerobic AOB to NO_(3)^(-)(0–5 cm),and Fe^(2+)is oxidized by microaerobic FeRB to Fe^(3+)(3–10 cm).In the denitrification/iron reduction zone,Acinetobacter and Pseudomonas,as the dominant NRB genera,may use nitrate as an electron acceptor to oxidize Fe^(2+)(11–16 cm).The dominant genera in SOB,such as Sulfururvum,Thiobacillus and Thioalkalispira,may use nitrate as an electron acceptor to oxidize sulfide,leading to SO_(4)^(2-)accumulation(14–24 cm).In the sulfate reduction zone,SO_(4)^(2-)is reduced by SRB.This study found that functional microorganisms forming comprehensive local ecological structures to adapt to changing geochemical conditions,and which would be potentially important for the degradation and preservation of C and the fate of many nutrients and contaminants in reservoirs.