| The GFDL Earth System Model version 4.1 (GFDL‐ESM 4.1): Overall coupled model description and simulation characteristics JP Dunne, LW Horowitz, AJ Adcroft, P Ginoux, IM Held, JG John, ... Journal of Advances in Modeling Earth Systems 12 (11), e2019MS002015, 2020 | 426 | 2020 |
| NOAA-GFDL GFDL-ESM4 model output prepared for CMIP6 C4MIP esm-ssp585 JP Krasting, C Blanton, C McHugh, A Radhakrishnan, JG John, K Rand, ... World Data Center for Climate (WDCC) at DKRZ, 2018 | 139 | 2018 |
| NOAA-GFDL GFDL-CM4 model output historical H Guo, JG John, C Blanton, C McHugh, S Nikonov, A Radhakrishnan, ... Earth System Grid Federation. https://doi. org/10.22033/ESGF/CMIP6 8594, 2018 | 65 | 2018 |
| NOAA-GFDL GFDL-ESM4 model output prepared for CMIP6 CMIP historical, Earth System Grid Federation JP Krasting, JG John, C Blanton, C McHugh, S Nikonov, A Radhakrishnan, ... | 11 | 2018 |
| NOAA-GFDL GFDL-ESM4 model output prepared for CMIP6 CMIP. Earth System Grid Federation JP Krasting, JG John, C Blanton, C McHugh, S Nikonov, A Radhakrishnan, ... | 9 | 2018 |
| NOAA-GFDL GFDL-CM4 model output prepared for CMIP6 CMIP H Guo, JG John, C Blanton, C McHugh, S Nikonov, A Radhakrishnan, ... Earth System Grid Federation, 2018 | 5 | 2018 |
| 555 Silvers JP Krasting, JG John, C Blanton, C McHugh, S Nikonov, A Radhakrishnan, ... L., Wyman, B., Zeng, Y., Adcroft, A., Dunne, JP, Dussin, R., Guo, H., He, J …, 0 | 5 | |
| NOAA-GFDL GFDL-CM4 model output prepared for CMIP6 CMIP historical, Earth System Grid Federation H Guo, JG John, C Blanton, C McHugh, S Nikonov, A Radhakrishnan, ... Technica l Report 10, 2018 | 4 | 2018 |
| Using Lomb–Scargle analysis to derive empirical orthogonal functions from gappy meteorological data C Dupuis, C Schumacher Journal of Applied Meteorology and Climatology 57 (10), 2217-2229, 2018 | 2 | 2018 |
| NOAA-GFDL GFDL-ESM4 model output prepared for CMIP6 LUMIP S Malyshev, C Blanton, C McHugh, K Rand, S Nikonov, A Radhakrishnan, ... World Data Center for Climate (WDCC) at DKRZ, 2018 | 1 | 2018 |
| The land component LM4. 1 of the GFDL Earth System Model ESM4. 1: Model description and characteristics of land surface climate and carbon cycling in the historical simulation E Shevliakova, S Malyshev, I Martinez‐Cano, PCD Milly, SW Pacala, ... Journal of Advances in Modeling Earth Systems 16 (5), e2023MS003922, 2024 | | 2024 |
| Generalizing Statistical Functions for Climate Model Machine Learning and Ensemble Consistency Tests C Dupuis AGU Fall Meeting Abstracts 2019, GC43D-1359, 2019 | | 2019 |
| EDGIer APIs: Scalable, Feature-Rich Empirical Orthogonal Function Analysis of Distributed Geoscientific Data That" Just Works" C Dupuis, C Bechtel, E Cruz AGU Fall Meeting Abstracts 2018, IN41D-0861, 2018 | | 2018 |
| Resampling Methods, Lomb-Scargle Analysis, and Empirical Orthogonal Functions: A Combined Approach to Gappy Data in the Maritime Continent C Dupuis, C Schumacher 98th American Meteorological Society Annual Meeting, 2018 | | 2018 |
| Accelerating the GFDL Climate Model for the Knights Landing Next-Generation Architecture C Dupuis 98th American Meteorological Society Annual Meeting, 2018 | | 2018 |
| IPCC DDC: NOAA-GFDL GFDL-CM4 model output amip H Guo, JG John, C Blanton, C McHugh, S Nikonov, A Radhakrishnan, ... World Data Center for Climate (WDCC) at DKRZ, 2018 | | 2018 |
| IPCC DDC: NOAA-GFDL GFDL-ESM4 model output prepared for CMIP6 CMIP historical JP Krasting, JG John, C Blanton, C McHugh, S Nikonov, A Radhakrishnan, ... World Data Center for Climate (WDCC) at DKRZ, 2018 | | 2018 |
| A Theoretically Lossless Method for Deriving Empirical Orthogonal Functions from Unevenly Sampled Data CM Dupuis | | 2016 |
| Time Dependence of Bathymetric Effects on Hurricane Storm Surge C Dupuis | | 2012 |
| Development of a large acceptance, tracking gas ionization chamber C Dupuis, JC Blackmon, LE Linhardt, M Matos, DW Bardayan, ... APS Meeting Abstracts 3, GB. 036, 2009 | | 2009 |
John P. KrastingPhysical Scientist, NOAA/GFDL, Princeton, NJVerified email at noaa.gov
