EVALUATION OF A REDUCED JACOBIAN CHEMICAL SOLVER

To allow the use of detailed chemical modules in three-dimensional glo bal forecast and climate models, it is necessary to have efficient and accurate solvers for the chemical species that allow for diurnal forc ing. The aim of this work was to develop a fast chemistry solver based on the implicit Euler finite difference approximation to the chemical continuity equation for a set of chemical species. This finite differ ence form of the continuity equation is appealing because of its mass- conserving properties. We employ two algorithms for solution: a basic Newton solver and a modification of this method, which we have dubbed the reduced Jacobian (RJ) solver. Both methods yield equivalent soluti ons, but the RJ solver can be 10 times more efficient on a scalar mach ine for fixed time stepping. Both methods are evaluated for accuracy a nd timing against the Gear solver. The RJ algorithm breaks the Jacobia n matrix into smaller units that may be solved more efficiently. To do this, we have made use of the interactiveness of ''family'' species. The reduction in computational time makes this method a good candidate for three-dimensional modeling of atmospheric chemistry. In this pape r we discuss the method and present a chemical box model comparison of these three techniques for a chemical set comprising O-x, HOx, N-x, C lOx, BrOx, and CH4 oxidation gas-phase chemistry, at various heights i n the atmosphere ranging from the upper troposphere to the mesosphere. We have also tested a modification that reduces errors at sunrise and sunset without seriously compromising the efficiency of the method. F rom our tests it would appear that the RJ solver is robust at all heig hts tested and should be readily adapted to other chemical mechanisms.