labs_title

Detectability of CO2 flux signals by a space-based lidar mission

D.M. Hammerling, S.R. Kawa, K. Schaefer, S. Doney, and A.M. Michalak

As the need to monitor both the natural and anthropogenic components of the carbon cycle increases, there is an growing push towards the development of satellite remote-sensing platforms that can observe global atmospheric CO2 distributions with high precision and accuracy. One such platform is the active sensing of CO2 emissions over nights, days, and seasons (ASCENDS) satellite, a space-based lidar mission proposed as part of the NRC decadal survey. Here we examine the ability of such a mission to detect regional changes in CO2 emissions and uptake, through three prototypical case studies, namely, the thawing of permafrost in the northern high latitudes, the shifting of fossil fuel emissions from Europe to China, and changes in the source/sink characteristics of the Southern Ocean. Results confirm that an ASCENDS-like mission would make key contributions to our understanding of the global carbon cycle.


Figure: Results for the fossil fuel experiments for medium measurement noise. First row: 3-month mapped CO2 signal (“3-month mapped”). Second row: Significance of the 3-month mapped CO2 signal (“3-month signific.”). Third row: Yearly mapped CO2 signal (“Yearly mapped”). Fourth row: Significance of the yearly mapped CO2 signal (“Yearly signific.”). The mapped signal is the difference between the mapped perturbation CO2 concentration and the mapped baseline CO2 concentration. The significance is the mapped signal divided by the uncertainty of the mapped signal. The values are discretized for improved visualization. Yellow, orange and dark red (light, medium and dark blue) represent areas where the mapped perturbation concentration is larger (smaller) than the mapped baseline concentration by more than one, two or three standard deviations, respectively, of the uncertainty of the mapped signal. The 3-month period is August through September.

Abstract

Satellite observations of carbon dioxide (CO2) offer novel and distinctive opportunities for improving our quantitative understanding of the carbon cycle. Prospective observations include those from space-based lidar such as the active sensing of CO2 emissions over nights, days, and seasons (ASCENDS) mission. Here we explore the ability of such a mission to detect regional changes in CO2 fluxes. We investigate these using three prototypical case studies, namely, the thawing of permafrost in the northern high latitudes, the shifting of fossil fuel emissions from Europe to China, and changes in the source/sink characteristics of the Southern Ocean. These three scenarios were used to design signal detection studies to investigate the ability to detect the unfolding of these scenarios compared to a baseline scenario. Results indicate that the ASCENDS mission could detect the types of signals investigated in this study, with the caveat that the study is based on some simplifying assumptions. The permafrost thawing flux perturbation is readily detectable at a high level of significance. The fossil fuel emission detectability is directly related to the strength of the signal and the level of measurement noise. For a nominal (lower) fossil fuel emission signal, only the idealized noise-free instrument test case produces a clearly detectable signal, while experiments with more realistic noise levels capture the signal only in the higher (exaggerated) signal case. For the Southern Ocean scenario, differences due to the natural variability in the El Niño–Southern Oscillation climatic mode are primarily detectable as a zonal increase.

Hammerling, D.M., S.R. Kawa, K. Schaefer, S. Doney, A.M. Michalak (2015), "Detectability of CO2 flux signals by a space-based lidar mission", Journal of Geophysical Research – Atmospheres, 120 (5), 1794-1807, doi:10.1002/2014JD022483.