Assessment of Stratospheric Dropsonde Data through NWP Model Comparisons

Abstract: Recent advances have allowed for the development and deployment of lightweight, stratospherically launched micro-dropsondes; designed for release from navigable high-altitude balloons and other high-altitude “pseudo-satellite” systems. Such platforms have great potential to provide critical observations in data-sparse regions, particularly over oceanic and polar regions, provided their data are of sufficient quality. This work examines the quality of observations from the StratoSonde® system, developed by Voltitude Ltd., during a recent field campaign launching from Cabo Verde. The system offers the unique ability to manoeuvre to specific locations and schedule dropsonde deployments to observe developing severe weather systems.

Over a ten-day period, nine dropsonde descents were conducted over the mid-Atlantic, with an additional two descents carried out over the UK in a separate test flight. These descent profiles, recording pressure, temperature, dew point, humidity, and wind speed/direction, were assessed in a multi-model comparison using interpolated profiles from the Met Office's deterministic and ensemble numerical weather prediction models to assess the quality and reliability of the micro-dropsonde data.

Overall, the system performance was shown to be robust, with observations having generally low biases & root mean squared errors compared to all three models. Observations of temperature and winds had the smallest differences with respect to the models, however some greater differences were identified in the relative humidity data in the upper troposphere. Work to address this issue is now ongoing, with further trials – including co-located radiosonde ascents – planned for the near future.

This research contributes valuable insights into the potential for a combined HAB and micro-dropsonde system to deliver atmospheric profiles in remote regions, highlighting their strengths and identifying areas for improvement. The continued refinement of these systems holds promise for enhancing our understanding of atmospheric dynamics in previously under-sampled areas, and in advancing our ability to monitor and forecast potentially severe weather systems.

Biography: Matthew is a Scientist in the Met Office's Observation Network Design team, working to assess the potential of a variety of novel and third-party observations in meeting high priority observational requirements.