An Interpolation Method to Reduce the Computational Time in the Stochastic Lagrangian Particle Dispersion Modeling of Spatially Dense XCO₂ Retrievals.

ABSTRACT: A growing constellation of satellites is providing near-global coverage of column-averaged CO₂ observations. Launched in 2019, NASA's OCO-3 instrument is set to provide XCO₂ observations at a high spatial and temporal resolution for regional domains (100 × 100 km). The atmospheric column version of the Stochastic Time-Inverted Lagrangian Transport (X-STILT) model is an established method of determining the influence of upwind sources on column measurements of the atmosphere, providing a means of analysis for current OCO-3 observations and future space-based column-observing missions. However, OCO-3 is expected to provide hundreds of soundings per targeted observation, straining this already computationally intensive technique. This work proposes a novel scheme to be u

SUBMITTER: Roten D 

PROVIDER: S-EPMC8047910 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature