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

Abstract

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.

The Midlatitude Continental Convective Clouds Experiment (MC3E) sounding network: operations, processing and analysis

“…Figure 5 shows that although the differences between GPS, MWR and corrected sounding PWV are within expected bounds, the GPS PWV is biased low compared to the MWR and corrected soundings. A similar dry bias in GPS PWV relative to soundings and MWR estimates of PWV was noted at several sites in a recent tropical field campaign (AMIE-ARM MJO Investigation Experiment) conducted over the Indian Ocean and west- ern Pacific warm pool region (Ciesielski et al, 2014). Due to this dry bias in the GPS observations, estimates of GPS PWV were not used to scale the extended site radiosonde observations.…”

Modes of vertical thermodynamic and wind variability over the Maritime Continent

“…4b. The specific radiosonde equipment, accuracy, and observational biases from each MC site were documented in Ciesielski et al (2014). The Ranai and Puerto Princesa sites used the same equipment throughout the study period, while the Singapore site switched sonde type in 2011.…”

“…Humidity measurements are the most uncertain, although several constant bias correction techniques are available for the equipment used at the three MC sites. For this study, either the sonde type was reported as precise enough for scientific research (Wang and Zhang, 2008;Ciesielski et al, 2014) or a form of mean/constant bias correction is available to improve their accuracy (Wang et al, 2013;Nuret et al, 2008). Because the instrument error is consistent among the three sites (P. E. Ciesielski, personal communication, 2016), any biases that exist in the radiosonde data will not propagate into the EOF/PCA, which quantifies system variability and is indifferent to mean quantities or biases therein.…”

“…First, in order to remove poor logarithmic interpolations resulting from extended gaps in reporting levels, the maximum and minimum data points for each 10 hPa level were examined and vertical profiles with extreme values were discarded. Second, every Skew-T/Log-P diagram of the raw data sounding was visually inspected (Ciesielski et al, 2014) prior to dataset formation and questionable profiles not caught by the criteria in Table 1 were excluded. The final number of observations for temperature, relative humidity, and winds for the three upper-air sounding sites is listed in Table 2.…”

The heated condensation framework as a convective trigger in the NCEP Climate Forecast System version 2

“…Figure 2 shows a comparison between the HCFv2 trigger and the original SAS trigger (pressure difference) applied to temperature and humidity profiles from radiosonde data from the Dynamics of the Madden Julian Oscillation (DYNAMO) project [Ciesielski et al, 2014]. The skill scores were calculated considering all radiosondes available for the 28 locations listed in Figure 2d.…”