Kumar, S., J. Kolassa, R. Reichle, et al. 2022. An Agenda for Land Data Assimilation Priorities: Realizing the Promise of Terrestrial Water, Energy, and Vegetation Observations From Space Journal of Advances in Modeling Earth Systems 14 (11):
e2022MS003259
[10.1029/2022ms003259]
MacBean, N., H. Liddy, T. Quaife, J. Kolassa, and A. Fox. 2022. Building a Land Data Assimilation Community to Tackle Technical Challenges in Quantifying and Reducing Uncertainty in Land Model Predictions Bulletin of the American Meteorological Society 103 (3):
E733-E740
[10.1175/bams-d-21-0228.1]
Weir, B., D. Crisp, C. W. O’Dell, et al. 2021. Regional impacts of COVID-19 on carbon dioxide detected worldwide from space Science Advances 7 (45):
eabf9415
[10.1126/sciadv.abf9415]
Alemohammad, S. H., J. Kolassa, C. Prigent, F. Aires, and P. Gentine. 2018. Global Downscaling of Remotely-Sensed Soil Moisture using Neural Networks Hydrology and Earth System Sciences Discussions 1-19
[10.5194/hess-2017-680]
Alemohammad, S. H., B. Fang, A. G. Konings, et al. 2017. Water, Energy, and Carbon with Artificial Neural Networks (WECANN): a statistically based estimate of global surface turbulent fluxes and gross primary productivity using solar-induced fluorescence Biogeosciences 14 (18):
4101-4124
[10.5194/bg-14-4101-2017]
Kolassa, J., P. Gentine, C. Prigent, F. Aires, and S. Alemohammad. 2017. Soil moisture retrieval from AMSR-E and ASCAT microwave observation synergy. Part 2: Product evaluation Remote Sensing of Environment 195 202-217
[10.1016/j.rse.2017.04.020]
Green, J. K., A. G. Konings, S. H. Alemohammad, et al. 2017. Regionally strong feedbacks between the atmosphere and terrestrial biosphere Nature Geoscience
[10.1038/ngeo2957]
Kolassa, J., P. Gentine, C. Prigent, and F. Aires. 2016. Soil moisture retrieval from AMSR-E and ASCAT microwave observation synergy. Part 1: Satellite data analysis Remote Sensing of Environment 173 1-14
[10.1016/j.rse.2015.11.011]
Rodriguez-Fernandez, N. J., F. Aires, P. Richaume, et al. 2015. Soil Moisture Retrieval Using Neural Networks: Application to SMOS IEEE Transactions on Geoscience and Remote Sensing 53 (11):
5991-6007
[10.1109/tgrs.2015.2430845]
Foley, A. M., D. Dalmonech, A. D. Friend, et al. 2013. Evaluation of biospheric components in Earth system models using modern and palaeo-observations: the state-of-the-art Biogeosciences 10 (12):
8305-8328
[10.5194/bg-10-8305-2013]
Jiménez, C., D. B. Clark, J. Kolassa, F. Aires, and C. Prigent. 2013. A joint analysis of modeled soil moisture fields and satellite observations Journal of Geophysical Research: Atmospheres 118 (12):
6771-6782
[10.1002/jgrd.50430]
Kolassa, J., F. Aires, J. Polcher, et al. 2013. Soil moisture retrieval from multi-instrument observations: Information content analysis and retrieval methodology Journal of Geophysical Research: Atmospheres 118 (10):
4847-4859
[10.1029/2012jd018150]