Improving the Estimation of the Atmospheric Water Vapor Pressure Using Interpretable Long Short-Term Memory Networks: Dataset, Python code, and trained models

• Main Authors: Bo Gao, Ethan Coon, Peter Thornton, Dan Lu
• Format: Dataset
• Language: unknown
• Published: ESS-DIVE: Deep Insight for Earth Science Data 2023
• Subjects: Atmospheric humidity; Atmospheric water vapor pressure; Long Short-term Memory; Static attributes; Interpretable deep learning; Fairbanks; Canada; Pacific; Kendall; Boreas; Brooklyn; Gulch; Monroe; Corral; Woodward; Goodwin; Washburn; Tombstone; The Bluff; Sherman Island; Reno; Merritt Island; Barrow; Brooks Range; glacier; glacier*; Tundra; Alaska
• Online Access: https://search.dataone.org/view/ess-dive-993a2817d456629-20231122T152659004

Atmospheric water vapor pressure is an essential meteorological control on land surface and hydrologic processes. It is not as frequently observed as other meteorologic conditions, but often inferred through the August–Roche–Magnus formula by simply assuming dew point and daily minimum temperatures...