| Analysis of climate signals in the crop yield record of sub‐Saharan Africa AL Hoffman, AR Kemanian, CE Forest Global change biology 24 (1), 143-157, 2018 | 99 | 2018 |
| The response of maize, sorghum, and soybean yield to growing-phase climate revealed with machine learning AL Hoffman, AR Kemanian, CE Forest Environmental Research Letters 15 (9), 094013, 2020 | 58 | 2020 |
| Estimating the sensitivity of regional dust sources to sea surface temperature patterns AL Hoffman, CE Forest, W Li Journal of Geophysical Research: Atmospheres 119 (17), 10,160-10,174, 2014 | 9 | 2014 |
| Fast parameter estimation of generalized extreme value distribution using neural networks S Rai, A Hoffman, S Lahiri, DW Nychka, SR Sain, S Bandyopadhyay arXiv preprint arXiv:2305.04341, 2023 | 6 | 2023 |
| Detecting the Effect of Dust and Other Climate Variables on Crop Yields Using Diagnostic Statistical Crop Models AL Hoffman The Pennsylvania State University, 2018 | 2 | 2018 |
| Disentangling the Response of Corn, Sorghum and Soybean to Climate Variables in the United States. AL Hoffman, AR Kemanian, CE Forest ASA, CSSA, and CSA International Annual Meeting (2018), 2018 | 1 | 2018 |
| Climate Services to Help Conservation of Critical Ecosystems and Climate Change Adaptation in Colombia J Delgado, EC Weatherhead, G Armenta, MC Ramos, M Evans, ... 103rd AMS Annual Meeting, 2023 | | 2023 |
| Downscaling Global Heat Exposure Metrics to Subkilometer Resolutions EA Middlemas, LE Madaus, G Yacalis, S Sain, AL Hoffman 102nd American Meteorological Society Annual Meeting, 2022 | | 2022 |
| Understanding Global Wildfire Risk across Historical and Future Scenarios in CMIP6 A Hoffman, LE Madaus 102nd American Meteorological Society Annual Meeting, 2022 | | 2022 |
| Flexible Python-Based Statistical Workflow for Flood Risk Estimates Applied across CMIP6 Models AL Hoffman, S Sain, J Jacobson 101st American Meteorological Society Annual Meeting, 2021 | | 2021 |
| From Operational to Planning: Fire and Fire Risk Predictions across Scales JP Hacker, C Smith, AL Hoffman, A Jordi 101st American Meteorological Society Annual Meeting, 2021 | | 2021 |
| Applications of Artificial Intelligence to the Coastal Environment; Artificial Intelligence Applied to Remote Sensing G Dusek, J Feyen, P Tissot, S Sain, AL Hoffman 101st American Meteorological Society Annual Meeting, 2021 | | 2021 |
| Flexible methodology for hyperlocal flooding risk due to sea level rise A Hoffman, SR Sain, J Jacobson AGU Fall Meeting Abstracts 2020, NH038-0011, 2020 | | 2020 |
| What can crop modelers learn from machine learning models about corn, sorghum and soybean? A Kemanian, A Hoffman, F Chris ICROPM2020: Second International Crop Modelling Symposium, 2020 | | 2020 |
| Machine Learning Downscaling of Extreme Heat Events in New York City A Hoffman, L Madaus, J Pullen, J Hacker 100th American Meteorological Society Annual Meeting, 2020 | | 2020 |
| Estimating the impact of mineral aerosols on crop yields in food insecure regions using statistical crop models A Hoffman, CE Forest, A Kemanian AGU Fall Meeting Abstracts 2016, A14C-08, 2016 | | 2016 |
| Estimating the Sensitivity of Regional Dust Sources to Sea Surface Temperature Anomaly Patterns A Hoffman, CE Forest AGU Fall Meeting Abstracts 2014, A44C-04, 2014 | | 2014 |
| Estimating the Impact of Sea Surface Temperature Patterns on Mineral Aerosol Emission and Deposition AL Hoffman | | 2013 |
| Uncertainty quantification of regional climate change based on structural uncertainty in atmospheric GCMs CE Forest, W Li, CY Tsai, A Hoffman, J Barsugli, T Wagener, E Monier AGU Fall Meeting Abstracts, 2012 | | 2012 |
Chris E ForestProfessor, Pennsylvania State UniversityVerified email at psu.edu
