INM-RSHU Chemistry-Climate Model 0-120 km

• Main Authors: Sergei, Smyshlyaev, Vener, Galin, Volodin Evgenii
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Zenodo 2019
• Subjects: Atmosphere; Numerical modeling; Chemistry; Climate; Hines; Laplace; polar night
• Online Access: https://dx.doi.org/10.5281/zenodo.3555478; https://zenodo.org/record/3555478

Chemistry-Climate Model of the Low and Middle Atmosphere, developed at the Institute of Numerical Mathematics RAS and Russian State Hydrometeorological University (INM-RSHU CCM) Brief description The coupled global three-dimensional chemistry–climate model of the INM RAS and RSHU consists of two modules: a dynamic module (developed at the INM RAS) and photochemical module (developed at the RSHU) (Galin et al., 2007). Both modules have a long history of development and successful application in a number of well-known international projects on studying the climate, atmospheric gas composition, and their changes. The INM-RSHU CCM main components and data flow are illustrated in Figure 1. Dynamical Module (General Circulation Model of INM RAS) The equations of atmospheric hydrodynamics are solved by the finite-difference method on a C grid. The finite-difference approximation of the equations for horizontal velocities is performed in the advective form. The equations for horizontal transport written in the advective rather than divergent form make it possible to use a semi-implicit calculation scheme with a large time step, which leads to a significant enhancement of the computational performance by the model and to more appropriate results. Formally, this scheme has no integral conservation laws. However, the experience of numerical experiments shows that the systematic violation of the conservation law for the integral energy and angular momentum in the scheme is small and has no significant effect on the integration results. The prognostic variables of the GCM are wind, temperature, specific humidity, and surface pressure. The radiation module is based on the delta-Eddington approximation for calculating heat influxes to atmospheric layers (Galin et al. 2003). The shortwave radiative transfer is calculated starting from a wavelength of 200 nm. The ozone absorption bands in the range between 200 and 700 nm include 8 of a total of 18 spectral intervals used in the model. The model resolution is 5°x4° in longitude and latitude, with 39 levels vertically from the Earth’s surface up to 0.003 hPa. For the stratosphere and mesosphere, the vertical grid resolution is about 3 km. The time integration is conducted by a central-difference scheme combined with a semi-implicit scheme (gravity waves are treated implicitly). The time step is 12 min. To avoid numerical instability for polar areas, we use Fourier filtering for prognostic variables along a latitude circle. In addition, at each time step, the horizontal diffusion in the form of a fourth-order Laplace operator with a constant coefficient is used. This diffusion serves as a filter suppressing high spatial frequencies. The effect of this filter is substantial for ozone dynamics in the model [Galin et al, 2007]. The model also incorporates parameterizations of deep and shallow convection [Volodin and Schmitz, 2001] and orographic [Hines, 1997a] and nonorographic [Hines, 1997b] gravity-wave dumping. The parameterization of the gravity-wave dumping includes the transport of momentum and energy by gravity waves, which are generated predominantly in the troposphere and break down in higher layers (in the stratosphere and mesosphere). The model uses a parameterization of the second type (nonorographic dumping), which considers gravity waves generated by vertical wind shear and convection. The nonorographic wave resistance is exceptionally substantial for models of the upper stratosphere and especially the mesosphere, where the breaking of gravity waves has a decisive influence on the mean flow. 1.2. Chemical Module (RSHU CTM). The chemical module incorporates 74 basic atmospheric gas constituents directly or indirectly influencing the rates of a photochemical change in ozone. The model takes into account reactions of the oxygen, hydrogen, nitrogen, chlorine, bromine, and sulfur cycles, which makes is possible to treat the influence of chemical processes on the formation and evolution of not only ozone and the related gases but also the atmospheric sulfate aerosol. The list of model gases, photochemical and heterogeneous processes corresponds to that considered in (Smyshlyaev et al., 1998) with additional reactions of the sulfur cycle, influencing the formation of stratospheric sulfate aerosol [DeZafra and Smyshlyaev, 2001]. The number and type of the photochemical reactions used in the model allow to investigate variations in the main ozonerelated gases in the stratosphere, troposphere, and mesosphere. (Smyshlyaev et al., 1998). The system of transport equations for the mixing ratios of atmospheric trace gases with photochemical transformations in the RSHU CTMl is solved for 30 long-lived species and five families (oxygen, nitrogen, chlorine, bromine, and sulfur). The number of equations is determined from the relation between photochemical lifetimes of gas constituents and time constants of atmospheric transport. If these times for some gas are comparable or a photochemical lifetime exceeds the time constant of atmospheric transport, this gas is treated with a complete equation of transport with a stiff chemical interaction with other gases. For gases with chemical lifetimes considerably lower than the characteristic lifetime of atmospheric transport, a system of stiff equations is solved without transport of these gases by the atmospheric circulation. The equations for transport of long-lived trace gases are solved by the second order moments solving method (Prather 1986) with the option to use Semi-Lagrangian or Leap-Frog methods, while the stiff equations of the chemistry module are treated with autonomous, special-purpose algorithms designed for solving stiff problems [Smyshlyaev et al., 1998]. These are the so-called A-stable methods for solving stiff systems, when the solutions at explicit and implicit steps are taken to have distinct weighting factors. The heterogeneous chemistry treatment is based on the combination of the thermodynamics of phase transitions and the microphysics of particle size distribution and gravity settling to estimate the polar stratospheric clouds (PSCs) formation and evolution (Carslaw, 1995). The main assumption is that PSC particles are generated from the sulfate aerosol existing in the stratosphere as a result of uptake of nitrous oxide and water vapor (Tabazadesh et al., 1994). The resulting ternary aerosol consists of water vapor, sulfuric acid, and nitric acid. This assumption is confirmed by measurement data indicating that, at low temperatures of the polar night, the number of particles per unit volume remains almost the same as it has been prior to the polar night; however, the particles grow in size. The change in the composition and volume of the ternary aerosol, as well as the of water vapor and nitrous oxide and sulfuric acid vapors, was calculated by the parameterization [Carslaw, 1995], depending on the temperature and total volume content of H2O, HNO3, and H2SO4. Further evolution of the ternary aerosol is investigated, and its surface area is calculated on the basis of the lognormal particle size distribution from experimental data [Smyshlyaev et al., 2010]. On the basis of the measurement data, which indicate that, during PSC formation, the number of particles per unit volume remains the same as the number of particles of sulfuric acid aerosol and their size increases, we disregard the microphysics of new-particle formation in the PSC module and assume a change in the mean aerosol radius through the condensation and evaporation of the aerosol-volume fraction that exceeds saturation values. In our model, which requires PSCs only for estimation of the degree of their influence on the concentrations of ozone and ozone-related gases and where the study of microphysical processes is not the main objective, this approach takes into consideration variations in the aerosol surface area without making the initially complex model of atmospheric chemistry and dynamics even more complicated. In addition, this model allows us to simulate the processes of denitrification and dehydration of the polar atmosphere, because an increase in the mean radius of particles leads to increased velocities of gravity settling, which are calculated depending on the particle radius and density [Smyshlyaev et al., 2010], and the process of denitrification becomes more intensified. 1.3. Coupling The algorithm of the coupled model is built so as to take into account the interaction between chemical and physical processes at each time step of the model. At the first stage of the time step, we calculate the fluxes of solar radiation in the bulk of the atmosphere at each geographic point for a given season and daytime. These fluxes are calculated with consideration for the current calculated values of ozone content in the upper and lower layers of the atmosphere and for light scattering by molecules and aerosol particles. The radiative transfer in the atmosphere is calculated with a technique based on a modified delta-Eddington scheme in the shortwave band of the solar spectrum [Dvortsov et al., 1992]. The solar spectrum is divided into some 80 detailed subintervals, which are dictated by the interaction of radiation with atmospheric gases according to photodissociation relations. In each of these intervals, the values of the direct and scattered radiation are calculated with allowance for the absorption of atmospheric gas constituents, scattering on aerosol particles, molecular scattering, and reflection from the underlying surface. Further, the calculated radiation fluxes are used to derive the photodissociation rates of the atmospheric gases involved in the chemical module for calculating the rates of their photochemical production and destruction. The rate constants of chemical reactions are estimated on the basis of the atmospheric temperature values calculated in the dynamic module. The rates of photochemical production and atmospheric mass transport (derived from the dynamic model) are used then to simulate the evolution of ozone content, water vapor, methane, nitrous oxide, freons, and other chemically and radiatively active and long-lived atmospheric gases. The concentrations of short-lived gases are calculated concurrently by the above-mentioned technique for solving the equations of chemical kinetics without atmospheric mass transport. The time steps in the dynamic and chemical modules are synchronized (12 min), which allows an automatic daytime calculation of the concentrations of chemically active gases. The ozone, water vapor, methane, nitrous oxide, and freons concentrations calculated in this way are used to calculate the fluxes of solar radiation and outgoing longwave radiation, which are included in the dynamic module for the estimation of variations in the temperature and wind velocity in the lower and middle atmosphere. The atmospheric gas concentrations and the values of temperature and wind velocity estimated in this way initialize the next time step of the coupled model. As a result, the interaction between chemical and physical processes passes to the next time layer, thus allowing one to estimate spatial and temporal variations in the content of atmospheric gases and temperature in accordance with the abovementioned stages. Thus, the models interact at each time step, on the one hand, by using the temperature and wind-velocity values calculated by the INM GCM in modeling the transport of trace gas and the rates of chemical reactions in the chemistry transport model (RSHU CTM) and, on the other hand, by using the ozone content calculated with the CTM for estimating the rates of atmospheric heating and cooling in the GCM, which influence variations in the temperature and wind velocity in the atmosphere. : Fortran code for chemistry-climate modeling : {"references": ["Galin, V.Ya., Smyshlyaev, S.P., and Volodin, E.M., Combined chemistry\u2013climate model of the atmosphere, Izv., Atmos. Ocean. Phys., 2007, vol. 43, no. 4, pp. 399\u2013412.", "Galin, V.Ya., Smyshlyaev, S.P., and Volodin, E.M., Combined chemistry\u2013climate model of the atmosphere, Izv., Atmos. Ocean. Phys., 2007, vol. 43, no. 4, pp. 399\u2013412.", "Smyshlyaev, S.P., Dvortsov, V.L., Geller, M.A., and Yudin, V.A., A two dimensional model with input parameters from a GCM: Ozone sensitivity to different formulation for the longitudinal temperature variation, J. Geophys. Res., 1998, vol. 103, pp. 28373\u201328387.", "Smyshlyaev, S.P., Galin, V.Ya., Shaariibuu, G., and Motsakov, M.A., Modeling the variability of gas and aerosol components in the stratosphere of polar regions, Izv., Atmos. Ocean. Phys., 2010, vol. 46, no. 3, pp. 265\u2013280."]}