A novel approach for determining source–receptor relationships in model simulations: a case study of black carbon transport in northern hemisphere winter

Abstract

A Gaussian process emulator is applied to quantify the contributions of local and remote emissions of black carbon to its concentrations in different regions using a Latin hypercube sampling strategy for emission perturbations in the offline version of the Community Atmosphere Model Version 5.1 (CAM5) simulations. The source–receptor relationships are computed based on simulations constrained by a standard free-running CAM5 simulation and the ERA-Interim reanalysis product. The analysis demonstrates that the emulator is capable of retrieving the source–receptor relationships based on a small number of CAM5 simulations without any modifications to the model itself. Most regions are found to be most susceptible to their local emissions. The emulator also finds that the source–receptor relationships are approximately linear, and the signals retrieved from the model-driven and reanalysis-driven simulations are very similar, suggesting that the simulated circulation in CAM5 resembles the assimilated meteorology in ERA-Interim. The robustness of the results provides confidence for application of the emulator to detect dose–response signals in the climate system.

Keywords

• Gaussian process
• emulation
• black carbon
• source–receptor
• CAM5