Quality-Controlled Upper-Air Sounding Dataset for DYNAMO/CINDY/AMIE: Development and Corrections

• Published in: Journal of atmospheric and oceanic technology Vol. 31; no. 4; pp. 741 - 764
• Main Authors: Ciesielski, Paul E., Yu, Hungjui, Johnson, Richard H., Yoneyama, Kunio, Katsumata, Masaki, Long, Charles N., Wang, Junhong, Loehrer, Scot M., Young, Kathryn, Williams, Steven F., Brown, William, Braun, John, Van Hove, Teresa
• Format: Journal Article
• Language: English
• Published: Boston American Meteorological Society 01.04.2014
• Subjects: Atmospheric sciences; Atmospherics; Drying; Heating; Humidity; Marine; Moisture; Networks; Oscillations; Rotating generators; Sondes; Sounding; Tropical environments; Indian Ocean; IE, Pacific; ISW, Indian Ocean; ASE, Africa
• ISSN: 0739-0572; 1520-0426
• DOI: 10.1175/JTECH-D-13-00165.1

The upper-air sounding network for Dynamics of the Madden–Julian Oscillation (DYNAMO) has provided an unprecedented set of observations for studying the MJO over the Indian Ocean, where coupling of this oscillation with deep convection first occurs. With 72 rawinsonde sites and dropsonde data from 13 aircraft missions, the sounding network covers the tropics from eastern Africa to the western Pacific. In total nearly 26 000 soundings were collected from this network during the experiment’s 6-month extended observing period (from October 2011 to March 2012). Slightly more than half of the soundings, collected from 33 sites, are at high vertical resolution. Rigorous post–field phase processing of the sonde data included several levels of quality checks and a variety of corrections that address a number of issues (e.g., daytime dry bias, baseline surface data errors, ship deck heating effects, and artificial dry spikes in slow-ascent soundings). Because of the importance of an accurate description of the moisture field in meeting the scientific goals of the experiment, particular attention is given to humidity correction and its validation. The humidity corrections, though small relative to some previous field campaigns, produced high-fidelity moisture analyses in which sonde precipitable water compared well with independent estimates. An assessment of operational model moisture analyses using corrected sonde data shows an overall good agreement with the exception at upper levels, where model moisture and clouds are more abundant than the sonde data would indicate.