Assessing the performance of GPS radio occultation measurements in retrieving tropospheric humidity in cloudiness: A comparison study with radiosondes, ERA-Interim, and AIRS data sets

Abstract

We assess the impact that the Global Positioning System radio occultations (GPSRO) measurements have on complementing different data sets in characterizing the lower-to-middle tropospheric humidity in cloudy conditions over both land and oceans using data from 1 August 2006 to 31 October 2006. We use observations from rawinsondes, Global Positioning System radio occultations (GPSRO), Atmospheric Infrared Sounder (AIRS), and the European Center for Medium-Range Weather Forecasts Reanalysis Interim (ERA-Interim). During the selected time period, Constellation Observing System for Meteorology, Ionosphere, and Climate data were not assimilated in ERA-Interim. From each data set, we estimate a zonally averaged tropospheric specific humidity profile at tropical, middle, and high latitudes. Over land, we use rawinsondes as the ground truth and quantify the specific humidity differences and root-mean-square-errors (RMSEs) of the GPSRO, AIRS, and ERA-Interim profiles. GPSRO are beneficial in retrieving lower tropospheric humidity than upper tropospheric profiles, due to their loss of sensitivity at high altitudes. Blending GPSRO with ERA-Interim produces profiles with smaller humidity biases outside the tropics, but GPSRO data do not improve the humidity RMSE when compared to rawinsondes. Combining GPSRO with AIRS leads to smaller humidity bias at the tropics and high latitudes, while reducing humidity's RMSEs. Over oceans, no rawinsonde information is available, and we use ERA-Interim as a reference. Combining GPSRO with AIRS leads to smaller humidity RMSEs than AIRS. We conclude that cross-comparisons and synergies among multi-instrument observations are promising in advancing our knowledge of the tropospheric humidity in cloudy conditions. GPSRO data can contribute to improving humidity retrievals over cloud-covered regions, especially over land and within the boundary layer.

On the comparisons of tropical relative humidity in the lower and middle troposphere among COSMIC radio occultations and MERRA and ECMWF data sets

“…Quantitatively, the RH error obtains a value smaller than 5 % in the lower troposphere and smaller than 9 % in the middle troposphere. These results are also in a very good agreement with Vergados et al (2014), who estimated a < 3 and < 8 % GPSRO RH retrieval error in the lower and middle troposphere with respect to collocated radiosondes at ±30 • , respectively, for a temperature error of ±1.0 K. Above 400 hPa, Fig. 5 shows an increase of the RH error up to 30 % at 300 hPa.…”

“…The maximum differences are found over the ITCZ location and can reach up to 30 %, suggesting that ECMWF underestimates the moisture budget of the ascending branch of the Hadley Cell circulation. Northward from the ITCZ and at higher altitudes, the disagreement between the two data sets diminishes and falls within the estimated GPSRO RH uncertainty errors (e.g., Vergados et al, 2014;Kursinski and Gebhardt, 2014), thus becoming statistically insignificant. In the upper troposphere, both ECMWF and GPSRO data sets capture properly the moisture budget of the ITCZ, although we start noticing small RH differences within the dry subsiding regions northward from the ITCZ.…”

“…Kursinski et al (1997), Rocken et al (1997), Kursinski and Hajj (2001), and Colard and Healey (2003) described the retrieval process of humidity profiles from GPSRO observations. Steiner et al (1999), Gorbunov and Kornblueh (2001), Divakarla et al (2006), Ho et al (2007), Chou et al (2009), Ho et al (2010, Sun et al (2010), Gorbunov et al (2011), Kishore et al (2011), Wang et al (2013, and Vergados et al (2014) validated the GPSRO-based humidity retrievals against reanalyses, radiosondes, and satellite observations, while recently Kursinski and Gebhardt (2014) reported an innovative technique to further reduce and eliminate retrieval biases in the middle-troposphere humidity products.…”

Comparisons of the tropospheric specific humidity from GPS radio occultations with ERA-Interim, NASA MERRA, and AIRS data

“…Ao et al (2012) estimated that the SH precision is ∼ 0.15 g kg −1 per degree K error in temperature. Vergados et al (2014) reported that RO SH is retrieved within ∼ 0.20-0.40 g kg −1 accuracy at the tropics, provided the RO refractivity accuracy is ∼ 1.0 % at an altitude of 2.0 km, decreasing to ∼ 0.2 % at an altitude of 8.0 km (Kuo et al, 2005) and a temperature error of ±1.0 K. Recently, Kursinski and Gebhardt (2014) proposed a novel approach to further improve the retrieved humidity accuracy and precision from RO observations in the middle troposphere.…”

Evaluating tropospheric humidity from GPS radio occultation, radiosonde, and AIRS from high-resolution time series

“…that N and p are constant: Ware et al (1996) showed that e could be estimated to within 0.25 hPa in the lower troposphere if temperature were known to within 1 K. Vergados et al (2014) depict the specific humidity retrieval errors due to temperature uncertainty for several latitude bands and pressure levels and show that humidity errors increase with increasing altitude and latitude, since humidity 20 decreases and thus its contribution to atmospheric refractivity. In the tropics (relevant for this study), the q uncertainty for 1 K T uncertainty is less than ±3 % below 700 hPa and increases to 18 % at 400 hPa (cut-off altitude in this study).…”