Jon Gottschalck
Biographic Data
| ID | 10282920 |
|---|---|
| NAME | Jon Gottschalck |
| GIVEN NAMES | Jon |
| FAMILY NAME | Gottschalck |
| SIGNATURE | GOTTSCHALCK J |
| AFFILIATIONS | NOAA Oceanic and Atmospheric Research |
| VERIFIED | No |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2004 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
User-Centered Design and Testing of Drought Forecast Visualizations to Improve Understanding and Decision-Making
Climate forecast visualizations can often be unintuitive, complicated to use, and difficult to understand. Using evidence from multidisciplinary social science research and a robust mixed-method approach, we collaborated with scientists and forecasters at the National Oceanic and Atmospheric Administration’s (NOAA) Climate Prediction Center and National Integrated Drought Information System (NIDIS) to redesign deterministic U.S. Drought Outlook f…
Using Visualization Science to Improve Expert and Public Understanding of Probabilistic Temperature and Precipitation Outlooks
Visually communicating temperature and precipitation climate outlook graphics is challenging because it requires the viewer to be familiar with probabilities as well as to have the visual literacy to interpret geospatial forecast uncertainty. In addition, the visualization scientific literature has open questions on which visual design choices are the most effective at expressing the multidimensionality of uncertain forecasts, leaving designers w…
The Global Land Data Assimilation System
A Global Land Data Assimilation System (GLDAS) has been developed. Its purpose is to ingest satellite- and ground-based observational data products, using advanced land surface modeling and data assimilation techniques, in order to generate optimal fields of land surface states and fluxes. GLDAS is unique in that it is an uncoupled land surface modeling system that drives multiple models, integrates a huge quantity of observation-based data, runs…
No prominent works on this page.
The Global Land Data Assimilation System
A Global Land Data Assimilation System (GLDAS) has been developed. Its purpose is to ingest satellite- and ground-based observational data products, using advanced land surface modeling and data assimilation techniques, in order to generate optimal fields of land surface states and fluxes. GLDAS is unique in that it is an uncoupled land surface modeling system that drives multiple models, integrates a huge quantity of observation-based data, runs…
Using Visualization Science to Improve Expert and Public Understanding of Probabilistic Temperature and Precipitation Outlooks
Visually communicating temperature and precipitation climate outlook graphics is challenging because it requires the viewer to be familiar with probabilities as well as to have the visual literacy to interpret geospatial forecast uncertainty. In addition, the visualization scientific literature has open questions on which visual design choices are the most effective at expressing the multidimensionality of uncertain forecasts, leaving designers w…
User-Centered Design and Testing of Drought Forecast Visualizations to Improve Understanding and Decision-Making
Climate forecast visualizations can often be unintuitive, complicated to use, and difficult to understand. Using evidence from multidisciplinary social science research and a robust mixed-method approach, we collaborated with scientists and forecasters at the National Oceanic and Atmospheric Administration’s (NOAA) Climate Prediction Center and National Integrated Drought Information System (NIDIS) to redesign deterministic U.S. Drought Outlook f…
Climate Change Communication and Perception (2 works) · Computer Science (2 works) · Data Visualization and Analytics (2 works) · Geography (2 works) · Geospatial analysis (2 works) · Graphics (2 works) · Remote sensing (2 works) · Artificial Intelligence (1 works) · Assimilation (phonology) (1 works) · Climate change (1 works)