Data Quality Control and Calibration for Mini-Radiosonde System “Storm Tracker” in Taiwan

This study reports the correction methods of a newly introduced upper-air radiosonde instrument, “Storm Tracker” (ST), with more than one thousand co-launches of ST and Vaisala RS41-SGP (VS) data in field observations in the Taiwan area during 2016-2022. The co-launches provided more than a million comparable independent observations of wind, pressure, temperature, and humidity (PTU) data. Using the VS measurements as the reference, we use the statistical models, including the cumulative distribution function (CDF) matching method and generalized linear model (GLM), to correct the temperature and moisture fields of the ST sounding. Both approaches yield similar results. With a sounding-by-sounding comparison, the CDF-corrected ST soundings have a 1-K temperature and 7 % relative humidity root mean square difference from the VS soundings. These error differences can be reduced to 0.66-K and 4.61 % below the 700-hPa height. The GPS estimated a 0.05 ms−1 ST wind difference from the VS sounding. The biases of the corrected ST observations are slightly larger than the random errors, which were 0.24 K and 2.21 % in the laboratory and 0.52 K and 2.23 % in the field. The lower atmosphere in a region of complex terrain may have large wind, temperature, and moisture variations. With the relatively low cost, a high proportion of successful launches, and accuracy of wind, temperature, and moisture, ST can complement regular upper-air radiosonde observations for high-resolution observations in the lower troposphere. The high-resolution lower troposphere observation is important for severe weather research in East Asia.