Daniel M. Ricciuto
Orcid: 0000-0002-3668-3021
According to our database1,
Daniel M. Ricciuto
authored at least 16 papers
between 2006 and 2023.
Collaborative distances:
Collaborative distances:
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Bibliography
2023
An ultrahigh-resolution E3SM land model simulation framework and its first application to the Seward Peninsula in Alaska.
J. Comput. Sci., November, 2023
2022
Guidelines for Publicly Archiving Terrestrial Model Data to Enhance Usability, Intercomparison, and Synthesis.
Data Sci. J., 2022
Improving net ecosystem CO2 flux prediction using memory-based interpretable machine learning.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2022
2020
Efficient Distance-based Global Sensitivity Analysis for Terrestrial Ecosystem Modeling.
Proceedings of the 20th International Conference on Data Mining Workshops, 2020
2019
Efficient surrogate modeling methods for large-scale Earth system models based on machine learning techniques.
CoRR, 2019
Learning-Based Inversion-Free Model-Data Integration to Advance Ecosystem Model Prediction.
Proceedings of the 2019 International Conference on Data Mining Workshops, 2019
An Efficient Bayesian Method for Advancing the Application of Deep Learning in Earth Science.
Proceedings of the 2019 International Conference on Data Mining Workshops, 2019
Proceedings of the Computational Science - ICCS 2019, 2019
2016
A scalable framework for the global offline community land model ensemble simulation.
Int. J. Comput. Sci. Eng., 2016
2015
Comput. Electron. Agric., 2015
2014
Stochastic Parameterization to Represent Variability and Extremes in Climate Modeling.
Proceedings of the International Conference on Computational Science, 2014
2013
Comput. Geosci., 2013
Proceedings of the International Conference on Computational Science, 2013
2012
Proceedings of the International Conference on Computational Science, 2012
2011
Proceedings of the Encyclopedia of Parallel Computing, 2011
2006
Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations.
IEEE Trans. Geosci. Remote. Sens., 2006