| Wind estimation in the lower atmosphere using multirotor aircraft RT Palomaki, NT Rose, M van den Bossche, TJ Sherman, SFJ De Wekker Journal of Atmospheric and Oceanic Technology 34 (5), 1183-1191, 2017 | 209 | 2017 |
| Analysis of random forest modeling strategies for multi-step wind speed forecasting D Vassallo, R Krishnamurthy, T Sherman, HJS Fernando Energies 13 (20), 5488, 2020 | 39 | 2020 |
| Characterizing the impact of particle behavior at fracture intersections in three-dimensional discrete fracture networks T Sherman, JD Hyman, D Bolster, N Makedonska, G Srinivasan Physical Review E 99 (1), 013110, 2019 | 37 | 2019 |
| A review of spatial Markov models for predicting pre-asymptotic and anomalous transport in porous and fractured media T Sherman, NB Engdahl, G Porta, D Bolster Journal of Contaminant Hydrology 236, 103734, 2021 | 32 | 2021 |
| Characterizing the influence of fracture density on network scale transport T Sherman, J Hyman, M Dentz, D Bolster Journal of Geophysical Research: Solid Earth 125 (1), e2019JB018547, 2020 | 27 | 2020 |
| A spatial Markov model for upscaling transport of adsorbing-desorbing solutes T Sherman, A Paster, G Porta, D Bolster Journal of contaminant hydrology 222, 31-40, 2019 | 25 | 2019 |
| Parameterizing the spatial Markov model from breakthrough curve data alone T Sherman, A Fakhari, S Miller, K Singha, D Bolster Water Resources Research 53 (12), 10888-10898, 2017 | 23 | 2017 |
| Subgrid theory for storm surge modeling AB Kennedy, D Wirasaet, A Begmohammadi, T Sherman, D Bolster, ... Ocean Modelling 144, 101491, 2019 | 21 | 2019 |
| A dual domain stochastic lagrangian model for predicting transport in open channels with hyporheic exchange T Sherman, KR Roche, DH Richter, AI Packman, D Bolster Advances in water resources 125, 57-67, 2019 | 21 | 2019 |
| Predicting downstream concentration histories from upstream data in column experiments T Sherman, A Foster, D Bolster, K Singha Water Resources Research 54 (11), 9684-9694, 2018 | 16 | 2018 |
| Characterizing reactive transport behavior in a three-dimensional discrete fracture network T Sherman, G Sole-Mari, J Hyman, MR Sweeney, D Vassallo, D Bolster Transport in Porous Media, 1-21, 2021 | 9 | 2021 |
| Upscaling transport of a sorbing solute in disordered non periodic porous domains T Sherman, EB Janetti, GR Guédon, G Porta, D Bolster Advances in Water Resources 139, 103574, 2020 | 8 | 2020 |
| Predicting vertical concentration profiles in the marine atmospheric boundary layer with a Markov chain random walk model HJ Park, T Sherman, LS Freire, G Wang, D Bolster, P Xian, A Sorooshian, ... Journal of Geophysical Research: Atmospheres 125 (19), e2020JD032731, 2020 | 6 | 2020 |
| Time-Series Forecasting Energy Loads: A Case Study in Texas R Rice, K North, G Hansen, D Pearson, O Schaer, T Sherman, D Vassallo 2022 Systems and Information Engineering Design Symposium (SIEDS), 196-201, 2022 | 3 | 2022 |
| Markovian Models for Microplastic Transport in Open‐Channel Flows L Xing, D Bolster, H Liu, T Sherman, DH Richter, K Rocha‐Brownell, Z Ru Water Resources Research 58 (8), e2021WR031746, 2022 | 2 | 2022 |
| Upscaling of Solute Plumes in Periodic Porous Media Through a Trajectory‐Based Spatial Markov Model E Bianchi Janetti, T Sherman, GR Guédon, D Bolster, GM Porta Water Resources Research 56 (12), e2020WR028408, 2020 | 2 | 2020 |
| Eighth Annual NOAA Open Data Dissemination K Duffy, M Robertson, T Lavoi, P Keown, T Sherman, R Chandra, N Merati, ... 103rd AMS Annual Meeting, 2023 | | 2023 |
| Machine learning methods for improving wind speed and wind energy production forecasting T Sherman 103rd AMS Annual Meeting, 2023 | | 2023 |
| Upscaling linear chemical reactions in porous media; a case study of Dry Creek, ID Z Sherman, T Sherman, D Bolster AGU Fall Meeting Abstracts 2022, H25P-1302, 2022 | | 2022 |
| Withdrawn: Interpretable Correction of HRRR Wind Speed Forecasts D Vassallo, T Sherman 102nd American Meteorological Society Annual Meeting, 2022 | | 2022 |
Diogo BolsterUniversity of Notre DameVerified email at nd.edu
