May 3, 2018
Journal: AGU Earth and Space Science
Authors: Jason English, Andrew Kren, Tanya Peevey
GSD/CIRES researchers investigated the impacts of removing satellite data and adding dropsonde data on weather forecasts in a study published in the AGU journal Earth and Space Science. The team used a technique known as an Observing System Simulation Experiment (OSSE). OSSEs are modeling experiments used to find out if a particular observing system will add value to numerical weather prediction analyses and forecasts when actual observational data is not available.
For this OSSE, researchers evaluated the impacts of removing US-based microwave and infrared satellite data from the Global Forecast System weather model. They compared GFS forecasts with a “truth” or nature run from an independent model that statistically simulates the real atmosphere. They found that removing satellite data significantly degrades forecasts averaged across large spatial scales. They also simulated the use of data from dropsondes deployed over a large “idealized” region of the Pacific and Arctic Oceans. This data improved forecasts averaged across large spatial scales, even when the satellite data is removed.
Researchers had mixed results with forecasts of three winter storms when satellite data was removed, but targeted dropsondes from a hypothetical flight campaign generally improved these forecasts.
These results suggest that targeted dropsondes cannot compensate for a gap in satellite data in global average forecasts, but may be able to compensate for specific targeted storms. However, many cases need to be studied before concluding with statistical confidence what impacts, if any, measurements (satellite, dropsonde, or other) have on forecasts of specific weather events. This work was completed with support of the NOAA Unmanned Aircraft Systems (UAS) Program as part of project Sensing Hazards with Operational Unmanned Technology (SHOUT).
For more information contact: Susan Cobb 303-497-5093