...
Abramowitz, G., Ukkola, A., Hobeichi, S., Cranko Page, J., Lipson, M., De Kauwe, M., Green, S., Brenner, C., Frame, J., Nearing, G., Clark, M., Best, M., Anthoni, P., Arduini, G., Boussetta, S., Caldararu, S., Cho, K., Cuntz, M., Fairbairn, D., Ferguson, C., Kim, H., Kim, Y., Knauer, J., Lawrence, D., Luo, X., Malyshev, S., Nitta, T., Ogee, J., Oleson, K., Ottlé, C., Peylin, P., de Rosnay, P., Rumbold, H., Su, B., Vuichard, N., Walker, A., Wang-Faivre, X., Wang, Y., and Zeng, Y.: On the predictability of turbulent fluxes from land: PLUMBER2 MIP experimental description and preliminary results, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-3084, 2024.
Aires, F., P. Weston, P. de Rosnay, D. Fairbairn, “ Statistical approaches to assimilate ASCAT soil moisture information: Part II Localisation strategy and evaluation”, QJRMS, submitted 2024
Fairbairn D., P. Weston, P. de Rosnay: "Evaluation of an Adaptive Soil Moisture Bias Correction Approach in the ECMWF Land Data Assimilation System", Remote Sensing 16(3), 2024, https://www.mdpi.com/2072-4292/16/3/493
Aires, F., P. Weston, P. de Rosnay, D. Fairbairn, “Statistical approaches to assimilate ASCAT soil moisture information: Part II Localisation strategy and evaluation”, in prep, 2023
Fan L., Y. Xiao; X. Li; G. De Lannoy; J. Peng; F. Frappart; A. Ebtehaj; P. de Rosnay; Z. Xing; Ling Yu; G. Dong; S. H. Yueh; J.-P. Wigneron: "Optimal land surface model's temperature inputs for global soil moisture and vegetation optical depth retrievals from SMAP", Remote Sensing of Env., in review, 2024
Herbert C., P. de Rosnay, P. Weston, and D. Fairbairn: Towards unified land data assimilation at ECMWF: Soil and snow temperature analysis in the SEKF, QJRMS in review 2024
Magnusson L., S. J. Majumdar, M. L. Dahoui, N. Bormann, M. Bonavita, P. A. Browne, A. R. Brown, G. De Chiara, D. I. Duncan, S. English, A. J. Geer, S. Healy, B. Ingleby, T. McNally, F. Pappenberger, F. Rabier, P. de Rosnay, M. P. Rennie, F. Warrick: “The role of observations in ECMWF tropical cyclone initialization and forecasting”, in review, QJRMS 2023
...