| ClimateNet: An expert-labelled open dataset and Deep Learning architecture for enabling high-precision analyses of extreme weather Prabhat, K Kashinath, M Mudigonda, S Kim, L Kapp-Schwoerer, ... Geoscientific Model Development Discussions 2020, 1-28, 2020 | 55 | 2020 |
| An overview of ARTMIP's Tier 2 Reanalysis Intercomparison: Uncertainty in the detection of atmospheric rivers and their associated precipitation ABM Collow, CA Shields, B Guan, S Kim, JM Lora, EE McClenny, K Nardi, ... Journal of Geophysical Research: Atmospheres 127 (8), e2021JD036155, 2022 | 48 | 2022 |
| Heat waves in Finland: present and projected summertime extreme temperatures and their associated circulation patterns S Kim, VA Sinclair, J Räisänen, R Ruuhela International Journal of Climatology 38 (3), 1393-1408, 2018 | 48 | 2018 |
| Detection uncertainty matters for understanding atmospheric rivers TA O’Brien, AE Payne, CA Shields, J Rutz, S Brands, C Castellano, ... Bulletin of the American Meteorological Society 101 (6), E790-E796, 2020 | 29 | 2020 |
| Atmospheric river lifecycle characteristics shaped by synoptic conditions at genesis S Kim, JCH Chiang International Journal of Climatology 42 (1), 521-538, 2022 | 8 | 2022 |
| Using deep learning for an analysis of atmospheric rivers in a high‐resolution large ensemble climate data set TB Higgins, AC Subramanian, A Graubner, L Kapp‐Schwoerer, ... Journal of Advances in Modeling Earth Systems 15 (4), e2022MS003495, 2023 | 4 | 2023 |
| Spatio-temporal segmentation and tracking of weather patterns with light-weight Neural Networks L Kapp-Schwoerer, A Graubner, S Kim, K Kashinath | 2 | 2020 |
| Atmospheric river representation in the Energy Exascale Earth System Model (E3SM) version 1.0 S Kim, LR Leung, B Guan, JCH Chiang Geoscientific Model Development 15 (14), 5461-5480, 2022 | 1 | 2022 |
| Untangling the Relationship Between AMOC Variability and North Atlantic Upper‐Ocean Temperature and Salinity JCH Chiang, W Cheng, WM Kim, S Kim Geophysical Research Letters 48 (14), e2021GL093496, 2021 | 1 | 2021 |
| Atmospheric Rivers: Genesis, Representation, and Structure S Kim University of California, Berkeley, 2023 | | 2023 |
| Using Deep Learning for a High-Precision Analysis of Atmospheric Rivers in a High-Resolution Large Ensemble Climate Dataset T Higgins, A Subramanian, A Graubner, L Kapp-Schwoerer, K Kashinath, ... EGU General Assembly Conference Abstracts, EGU22-1835, 2022 | | 2022 |
| Atmospheric River Representation in the Energy Exascale Earth System Model (E3SM) Version 1.0 S Kim, LR Leung, B Guan, JCH Chiang Geoscientific Model Development Discussions 2021, 1-25, 2021 | | 2021 |
