13 citations as recorded by crossref.

1. A CO2–Δ14CO2 inversion setup for estimating European fossil CO2 emissions C. Gómez-Ortiz et al. https://doi.org/10.5194/acp-25-397-2025
2. Computationally efficient methods for large-scale atmospheric inverse modeling T. Cho et al. https://doi.org/10.5194/gmd-15-5547-2022
3. Fundamentals of data assimilation applied to biogeochemistry P. Rayner et al. https://doi.org/10.5194/acp-19-13911-2019
4. Quantitative comparison of variational and sequential data assimilation techniques for one-dimensional initial-value problems of ideal MHD J. Arnal & C. Groth https://doi.org/10.1016/j.compfluid.2024.106373
5. Geostatistical inverse modeling with very large datasets: an example from the Orbiting Carbon Observatory 2 (OCO-2) satellite S. Miller et al. https://doi.org/10.5194/gmd-13-1771-2020
6. Impacts of Horizontal Resolution on Global Data Assimilation of Satellite Measurements for Tropospheric Chemistry Analysis T. Sekiya et al. https://doi.org/10.1029/2020MS002180
7. Using atmospheric trace gas vertical profiles to evaluate model fluxes: a case study of Arctic-CAP observations and GEOS simulations for the ABoVE domain C. Sweeney et al. https://doi.org/10.5194/acp-22-6347-2022
8. A global synthesis inversion analysis of recent variability in CO2 fluxes using GOSAT and in situ observations J. Wang et al. https://doi.org/10.5194/acp-18-11097-2018
9. Effect of Data Assimilation Parameters on The Optimized Surface CO2 Flux in Asia H. Kim et al. https://doi.org/10.1007/s13143-017-0049-9
10. Comparison between the Local Ensemble Transform Kalman Filter (LETKF) and 4D‐Var in atmospheric CO2 flux inversion with the Goddard Earth Observing System‐Chem model and the observation impact diagnostics from the LETKF J. Liu et al. https://doi.org/10.1002/2016JD025100
11. Comparing the CarbonTracker and TM5-4DVar data assimilation systems for CO2 surface flux inversions A. Babenhauserheide et al. https://doi.org/10.5194/acp-15-9747-2015
12. Length Scale Analyses of Background Error Covariances for EnKF and EnSRF Data Assimilation S. Park et al. https://doi.org/10.3390/atmos13020160
13. Global and regional carbon budget for 2015–2020 inferred from OCO-2 based on an ensemble Kalman filter coupled with GEOS-Chem Y. Kong et al. https://doi.org/10.5194/acp-22-10769-2022