| The CAMS greenhouse gas reanalysis from 2003 to 2020 A Agustí-Panareda, J Barré, S Massart, A Inness, I Aben, M Ades, ... Atmospheric Chemistry and Physics 23 (6), 3829-3859, 2023 | 31 | 2023 |
| Quantification of methane emissions from hotspots and during COVID-19 using a global atmospheric inversion J McNorton, N Bousserez, A Agustí-Panareda, G Balsamo, L Cantarello, ... Atmospheric Chemistry and Physics 22 (9), 5961-5981, 2022 | 28 | 2022 |
| Spatial interpolation of two‐metre temperature over Norway based on the combination of numerical weather prediction ensembles and in situ observations C Lussana, IA Seierstad, TN Nipen, L Cantarello Quarterly Journal of the Royal Meteorological Society 145 (725), 3626-3643, 2019 | 11 | 2019 |
| An idealized 1½-layer isentropic model with convection and precipitation for satellite data assimilation research. Part II: Model derivation O Bokhove, L Cantarello, S Tobias Journal of the Atmospheric Sciences 79 (3), 875-886, 2022 | 6 | 2022 |
| Idealized forecast-assimilation experiments for convective-scale Numerical Weather Prediction T Kent, L Cantarello, G Inverarity, S Tobias, O Bokhove EarthArXiv, 2020 | 6 | 2020 |
| An idealized 1½-layer isentropic model with convection and precipitation for satellite data assimilation research. Part I: Model dynamics L Cantarello, O Bokhove, S Tobias Journal of the Atmospheric Sciences 79 (3), 859-873, 2022 | 3 | 2022 |
| Modified shallow water models and idealised satellite data assimilation L Cantarello University of Leeds, 2021 | 2 | 2021 |
| Experiments with the modified Rotating Shallow Water model (modRSW, v. 1.0): assessing the relevance for convective-scale data assimilation research T Kent, L Cantarello, G Inverarity, S Tobias, O Bokhove Geoscientific Model Development Discussions 2022, 1-40, 2022 | 1 | 2022 |
| Idealised forecast-assimilation experiments and their relevance for convective-scale Numerical Weather Prediction. T Kent, G Inverarity, L Cantarello, S Tobias, O Bokhove Geophysical Research Abstracts 21, 2019 | 1 | 2019 |
| Flow-dependent observation errors for GHG inversions in an ensemble Kalman smoother M Steiner, L Cantarello, S Henne, D Brunner EGUsphere 2024, 1-24, 2024 | | 2024 |
| An idealized 1.5-layer isentropic model with convection and precipitationfor satellite data assimilation research. Part I: model dynamics L Cantarello, O Bokhove, S Tobias EarthArXiv, 2021 | | 2021 |
| An idealized data assimilation framework to study the impact of simulated satellite observations at different length scales L Cantarello, O Bokhove, G Inverarity, S Migliorini, S Tobias 101st American Meteorological Society Annual Meeting, 2021 | | 2021 |
| An idealized 1 O Bokhove, L Cantarello, S Tobias | | 2021 |
| An idealized 1 L Cantarello, O Bokhove, S Tobias | | 2021 |
| Idealised satellite data assimilation experiments with clouds and precipitation L Cantarello, O Bokhove, G Inverarity, S Migliorini, S Tobias EGU General Assembly Conference Abstracts, 332, 2020 | | 2020 |
| Modifications to an idealised data assimilation scheme for research in convective-scale satellite data assimilation. L Cantarello, O Bokhove, S Tobias, G Inverarity, S Migliorini Geophysical Research Abstracts 21, 2019 | | 2019 |
| An idealised setup for future experiments in satellite data assimilation research L Cantarello, O Bokhove, S Tobias, G Inverarity, S Migliorini | | |
| Analisi delle previsioni mensili mediante il modello GLOBO (ISAC-CNR) A Buzzi, DD Mastrangelo, L Cantarello | | |
| Investigating satellite radiance data assimilation at different scales in an idealised convective modelling framework L Cantarello, O Bokhove, S Tobias, GIL Cantarello, G Inverarity | | |
| Simulating idealised satellite radiance observations L Cantarello | | |
Cristian LussanaNorwegian Meteorological Institute在 met.no 的电子邮件经过验证
Cristian LussanaNorwegian Meteorological Institute在 met.no 的电子邮件经过验证
Thomas NipenNorwegian Meteorological Institute在 met.no 的电子邮件经过验证