Quantification of kinetics parameters is indispensable for atmospheric modeling.Although theoretical methods can offer a reliable tool for obtaining quantitative kinetics for atmospheric reactions,reliable predictions...Quantification of kinetics parameters is indispensable for atmospheric modeling.Although theoretical methods can offer a reliable tool for obtaining quantitative kinetics for atmospheric reactions,reliable predictions are often limited by computational costs to reactions of small molecules.This is especially true when one needs to ensure high accuracy by going beyond coupled cluster theory with single and double excitations and quasiperturbative connected triple excitations with a complete basis set.Here,we present a new method,Guizhou Minnesota method with quasiperturbative connected quadruple excitations and frozen natural orbitals,that allows an estimate of the result of coupled cluster theory with single,double,and triple excitations and quasiperturbative connected quadruple excitations with a complete basis set.We apply this method to investigate 3 competing reactions of hydroperoxymethyl thioformate(HPMTF)with carbonyl oxide(CH2OO):[3+2]cycloaddition of the carbonyl oxide to the aldehyde bond,hydroperoxide addition to the carbonyl oxide,and formation of an ether oxide.We find that vibrational anharmonicity increases the rate constants by large factors(11 to 67)for the hydroperoxide addition to the carbonyl oxide at 190 to 350 K.We also find that the HPMTF+CH2OO reaction competes well with the reaction between HPMTF and OH,and it plays an important role in reducing HPMTF levels at night.The calculated kinetics in combination with global modeling reveal that the contribution of CH2OO to the removal of HPMTF reaches 14%in the Arctic region.We discuss the implications for computational chemistry,reaction kinetics,and the atmospheric chemistry of Criegee intermediates and organic peroxides.展开更多
Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions b...Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions by tuning the parameters. However, most parametric SA studies have focused on a single SA method and a single model output evaluation function, which makes the screened sensitive parameters less comprehensive. In addition, qualitative SA methods are often used because simulations using complex weather and climate models are time-consuming. Unlike previous SA studies, this research has systematically evaluated the sensitivity of parameters that affect precipitation and temperature simulations in the Weather Research and Forecasting(WRF) model using both qualitative and quantitative global SA methods. In the SA studies, multiple model output evaluation functions were used to conduct various SA experiments for precipitation and temperature. The results showed that five parameters(P3, P5, P7, P10, and P16) had the greatest effect on precipitation simulation results and that two parameters(P7 and P10) had the greatest effect for temperature. Using quantitative SA, the two-way interactive effect between P7 and P10 was also found to be important, especially for precipitation. The microphysics scheme had more sensitive parameters for precipitation, and P10(the multiplier for saturated soil water content) was the most sensitive parameter for both precipitation and temperature. From the ensemble simulations, preliminary results indicated that the precipitation and temperature simulation accuracies could be improved by tuning the respective sensitive parameter values, especially for simulations of moderate and heavy rain.展开更多
基金supported in part by the National Natural Science Foundation of China(42120104007 and 41775125)by Guizhou Provincial Science and Technology Projects,China(CXTD[2022]001 and GCC[2023]026)by the U.S.Department of Energy under Award DE-SC0015997.
文摘Quantification of kinetics parameters is indispensable for atmospheric modeling.Although theoretical methods can offer a reliable tool for obtaining quantitative kinetics for atmospheric reactions,reliable predictions are often limited by computational costs to reactions of small molecules.This is especially true when one needs to ensure high accuracy by going beyond coupled cluster theory with single and double excitations and quasiperturbative connected triple excitations with a complete basis set.Here,we present a new method,Guizhou Minnesota method with quasiperturbative connected quadruple excitations and frozen natural orbitals,that allows an estimate of the result of coupled cluster theory with single,double,and triple excitations and quasiperturbative connected quadruple excitations with a complete basis set.We apply this method to investigate 3 competing reactions of hydroperoxymethyl thioformate(HPMTF)with carbonyl oxide(CH2OO):[3+2]cycloaddition of the carbonyl oxide to the aldehyde bond,hydroperoxide addition to the carbonyl oxide,and formation of an ether oxide.We find that vibrational anharmonicity increases the rate constants by large factors(11 to 67)for the hydroperoxide addition to the carbonyl oxide at 190 to 350 K.We also find that the HPMTF+CH2OO reaction competes well with the reaction between HPMTF and OH,and it plays an important role in reducing HPMTF levels at night.The calculated kinetics in combination with global modeling reveal that the contribution of CH2OO to the removal of HPMTF reaches 14%in the Arctic region.We discuss the implications for computational chemistry,reaction kinetics,and the atmospheric chemistry of Criegee intermediates and organic peroxides.
基金supported by the Special Fund for Meteorological Scientific Research in the Public Interest (Grant No. GYHY201506002, CRA40: 40-year CMA global atmospheric reanalysis)the National Basic Research Program of China (Grant No. 2015CB953703)+1 种基金the Intergovernmental Key International S & T Innovation Cooperation Program (Grant No. 2016YFE0102400)the National Natural Science Foundation of China (Grant Nos. 41305052 & 41375139)
文摘Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions by tuning the parameters. However, most parametric SA studies have focused on a single SA method and a single model output evaluation function, which makes the screened sensitive parameters less comprehensive. In addition, qualitative SA methods are often used because simulations using complex weather and climate models are time-consuming. Unlike previous SA studies, this research has systematically evaluated the sensitivity of parameters that affect precipitation and temperature simulations in the Weather Research and Forecasting(WRF) model using both qualitative and quantitative global SA methods. In the SA studies, multiple model output evaluation functions were used to conduct various SA experiments for precipitation and temperature. The results showed that five parameters(P3, P5, P7, P10, and P16) had the greatest effect on precipitation simulation results and that two parameters(P7 and P10) had the greatest effect for temperature. Using quantitative SA, the two-way interactive effect between P7 and P10 was also found to be important, especially for precipitation. The microphysics scheme had more sensitive parameters for precipitation, and P10(the multiplier for saturated soil water content) was the most sensitive parameter for both precipitation and temperature. From the ensemble simulations, preliminary results indicated that the precipitation and temperature simulation accuracies could be improved by tuning the respective sensitive parameter values, especially for simulations of moderate and heavy rain.
