Impact of Radiosonde Measurement Accuracy on Precipitation Type and Convective Weather Forecast

In order to accurately predict the future state of the atmosphere, it is essential to obtain an accurate, timely assessment of its current state.  Of particular importance is the vertical profile of the atmosphere at disparate locations. Radiosondes have long served as the fundamental method for retrieving profile data from the surface to altitudes in excess of 35 km, which includes the troposphere and a significant portion of the stratosphere. The data generated by radiosondes is not only a central input to numerical weather prediction, but also enables model validation, weather and climate studies, and real-time assessments of atmospheric instability (i.e. the potential for convective weather). The data also function as the benchmark against which other observations are compared. However, it is important to recognize that the quality of measurements from radiosondes or other vertical profiling instruments can impact the ability to properly distinguish the details associated with noteworthy atmospheric features including, but not limited to, temperature inversions, cloud layers, and ice formation. As such, this study evaluates and quantifies the impact of profile data accuracy and precision on the assessment and prediction of weather conditions, with particular focus on convective environments and precipitation.

The likelihood and strength of convection is of great importance in weather analysis and forecasting. Convective weather is routinely cited as a major factor in weather-related fatalities, property damage, and reductions in efficiencies across transportation networks. In this study, the effect of radiosonde accuracy on convective stability indices was investigated by analyzing and modifying data from 56 soundings taken in three geographical regions during severe convective weather outbreaks. Vaisala RS92 and RS41 soundings were used as baselines while simulated profiles were generated through small offsets in temperature and humidity. The results suggest that the prediction of severe convective weather is sensitive to relatively small humidity errors: a constant -4 % RH offset in humidity results in a 5 - 29 % mean relative change in key stability indices. The impact was more significant in borderline situations, when the evolution of convection had more uncertainty; for example, the CAPE index mean relative change increased to 49 %.

Precipitation type, especially in wintertime, is strongly affected by the temperature and humidity profile. As with convective weather, correctly forecasting precipitation type is essential in the protection of life and property, as well as operational effectiveness and efficiency in numerous sectors. Accordingly, the importance of radiosonde measurement accuracy on precipitation type was investigated through the use of case studies. Precipitation type sensitivity to data accuracy was explored by examining baseline sounding profiles and simulated profiles in which small errors were introduced. The case studies demonstrate that small inaccuracies in atmospheric profiles can alter the precipitation type. From an operational perspective, inaccurate precipitation type forecast can be costly.

In summary, this study demonstrates the fact that small errors in vertical profile measurements can potentially lead to significant assessment and forecast errors during high-impact weather events.