Search

The Geostationary Carbon Cycle Observatory (GeoCarb) will make measurements of greenhouse gases over the contiguous North and South American landmasses at daily temporal resolution. The extreme flexibility of observing from geostationary orbit induces an optimization problem, as operators must choose what to observe and when. The proposed scanning strategy for the GeoCarb mission tracks the sun's path from east to west and covers the entire area of interest in five coherent regions in the order of tropical South America east, tropical South America west, temperate South America, tropical North America, and temperate North America. We express this problem in terms of a geometric set cover problem, and use an incremental optimization (IO) algorithm to create a scanning strategy that minimizes expected error as a function of the signal-to-noise ratio (SNR). The IO algorithm used in this studied is a modified greedy algorithm that selects, incrementally at 5 min intervals, the scanning areas with the highest predicted SNR with respect to air mass factor (AF) and solar zenith angle (SZA) while also considering operational constraints to minimize overlapping scans and observations over water. As a proof of concept, two experiments are performed applying the IO algorithm offline to create an SNR-optimized strategy and compare it to the proposed strategy. The first experiment considers all landmasses with equal importance and the second experiment illustrates a temporary campaign mode that gives major urban areas greater importance weighting. Using a simple instrument model, we found that there is a significant performance increase with respect to overall predicted error when comparing the algorithm-selected scanning strategies to the proposed scanning strategy.

We investigate the ability of column-integrated trace gas measurements from a geostationary satellite to constrain surface fluxes at regional scale. The proposed geoCARB instrument measures CO2, CO and CH4 at a maximum resolution of 3 km east–west × 2.7 km north–south. Precisions are 3 ppm for CO2, 10 ppb for CO and 18 ppb for CH4. Sampling frequency is flexible. Here we sample a region at the location of Shanghai every 2 daylight hours for 6 days in June. We test the observing system by calculating the posterior uncertainty covariance of fluxes. We are able to constrain urban emissions at 3 km resolution including an isolated power-plant. The CO measurement plays the strongest role; without it our effective resolution falls to 5 km. Methane fluxes are similarly well-estimated at 5 km resolution. Estimating the errors for a full year suggests such an instrument would be a useful tool for both science and policy applications.