Abstract
Abstract. Emission inventories serve as crucial input for atmospheric chemistry transport models. To make them usable for a model simulation, they have to be pre-processed and, traditionally, provided as input files at discrete model time steps. In this paper, we present an “online” approach, which produces a minimal number of input data read-in at the beginning of a simulation and which handles essential processing steps online during the simulation. For this purpose, a stand-alone Python package “emiproc” was developed, which projects the inventory data to the model grid and generates temporal and vertical scaling profiles for individual emission categories. The package is also able to produce “offline” emission files if desired. Furthermore, we outline the concept of the online emission module (written in Fortran 90) and demonstrate its implementation in two different atmospheric transport models: COSMO-GHG and COSMO-ART. Simulation results from both modeling systems show the equivalence of the online and offline procedure. While the model run time is very similar for both approaches, input size and pre-processing time are greatly reduced when online emissions are utilized.
Highlights
Gridded and temporally varying emission fields are a critical input for three-dimensional atmospheric chemistry transport models (Matthias et al, 2018)
Name of tracer Type of 3D volume emissions: 0: no emissions 1: offline emissions 2: online emissions Type of temporal scaling 0: no temporal scaling 1: temporal scaling using hour-of-day, day-of-week and month-of-year 2: temporal scaling using hour-of-year List of categories s considered as sources of the tracer List of temporal profiles used for each element of ycatl List of vertical profiles used for each element of ycatl List of speciation factors per category
The Python tool prepares the input for the simulation, which consists of gridded emission maps per source category, and temporal and vertical emission profiles
Summary
Gridded and temporally varying emission fields are a critical input for three-dimensional atmospheric chemistry transport models (Matthias et al, 2018) Such emissions are obtained from an inventory and pre-processed for the model as external inputs, which are read-in during simulation at regular time steps. Meteorology-dependent emissions, such as emissions from residential heating depending on outdoor temperatures, can be incorporated more We present such an online emission module, which has been integrated into two different atmospheric transport models, both based on the regional numerical weather prediction and climate model COSMO (Consortium for Smallscale Modeling; Baldauf et al, 2011).
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