The sensitivity analysis of aerosol properties to carbon dioxide retrieval algorithm
Abstract:Although the concentrations of atmospheric carbon dioxide (CO2) have rapidly increased over the last 250 years, our current knowledge about carbon cycle is still insufficient. The Greenhouse Gases Observing SATellite (GOSAT) is the first satellite dedicated to measure atmospheric CO2 concentrations from space. Even though many studies to develop the CO2 retrieval algorithms are performed, there have been serious limitations in spatial coverage and uncertainties due to aerosols and thin cirrus clouds. To reduce the errors due to aerosols and improve data availability, the CO2 retrieval algorithms combined with aerosol retrieval algorithm using Thermal And Near infrared Sensor for carbon Observation-Cloud and Aerosol Imager (TANSO-CAI) will be developed.
In this study, we describe our ongoing CO2 retrieval algorithms using shortwave infrared channels of GOSAT and the characteristics of retrieved CO2 concentration have been studied using the realistic simulations. Realistic simulations using the Vector LInearized pseudo-spherical Discrete ORdinate radiative Transfer (VLIDORT) have been carried out and the simulated retrieval errors of CO2 have been calculated for a range of values of surface type, surface pressure, solar zenith angle and aerosol loading under the assumption that the retrieval has converged to the correct answer.
Especially, this study focuses on sensitivity studies of various state vectors on simulated CO2 retrieval errors. The sensitivity study has shown that the assumptions about aerosol-related parameters, such as vertical distribution and types of aerosols, have the most influence on simulated CO2 retrieval errors. These results can provide useful information to estimate the effects of aerosols properties on CO2 retrieval algorithm.