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

Abstract

Abstract. The spatial variability of the tropical tropospheric relative humidity (RH) throughout the vertical extent of the troposphere is examined using Global Positioning System Radio Occultation (GPSRO) observations from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission. These high vertical resolution observations capture the detailed structure and moisture budget of the Hadley Cell circulation. We compare the COSMIC observations with the European Center for Medium-range Weather Forecast (ECMWF) Reanalysis Interim (ERA-Interim) and the Modern-Era Retrospective analysis for Research and Applications (MERRA) climatologies. Qualitatively, the spatial pattern of RH in all data sets matches up remarkably well, capturing distinct features of the general circulation. However, RH discrepancies exist between ERA-Interim and COSMIC data sets that are noticeable across the tropical boundary layer. Specifically, ERA-Interim shows a drier Intertropical Convergence Zone (ITCZ) by 15-20 % compared to both COSMIC and MERRA data sets, but this difference decreases with altitude. Unlike ECMWF, MERRA shows an excellent agreement with the COSMIC observations except above 400 hPa, where GPSRO observations capture drier air by 5-10 %. RH climatologies were also used to evaluate intraseasonal variability. The results indicate that the tropical middle troposphere at ±5-25 • is most sensitive to seasonal variations. COSMIC and MERRA data sets capture the same magnitude of the seasonal variability, but ERA-Interim shows a weaker seasonal fluctuation up to 10 % in the middle troposphere inside the dry air subsidence regions of the Hadley Cell. Over the ITCZ, RH varies by maximum 9 % between winter and summer.

Assessment of global navigation satellite system (GNSS) radio occultation refractivity under heavy precipitation

“…The positive refractivity bias is associated with a combination of colder retrieved temperature with respect to analyses and a higher retrieved specific humidity than the one in the analyses. This is consistent with Vergados et al (2015), who showed that ERA-Interim is systematically drier than RO in the tropics. Also, the fact that a difference exists between the different analyses used for this study and that RO thermodynamic re-trievals depend on the analyses or reanalysis in use implies that a difference between the retrievals obtained by different processing centers will exist under such conditions if they use different analyses or reanalyses.…”

Tropospheric dry layers in the tropical western Pacific: comparisons of GPS radio occultation with multiple data sets

“…Advantages of the simple retrieval are its simplicity and ease of calculation, and its independence of model moisture (and thus independence from errors in model moisture). Vergados et al (2015) used the simple method for this reason, using ECMWF temperatures for the independent temperatures. Ware et al (1996) (Eqs.…”

“…RO data feature inherent high accuracy and precision, high vertical resolution (100 to 200 m), all-weather capability, and long-term stability (Anthes, 2011), making them highly valuable for studying a large number of atmospheric phenomena. Vergados et al (2015) studied the spatial variability of relative humidity (RH) from RO compared to ECMWF and MERRA (Modern-Era Retrospective analysis for Research and Applications), focusing on time-averaged seasonal behavior; these comparisons suggest an overall reliable behavior of RO-derived humidity fields. So far no study has focused on RO and extreme dryness (RH < 10 %).…”

Estimating observation and model error variances using multiple data sets

“…35 (6) The estimated error profiles are smallest for the ERA-Interim model data set, which is a reasonable result since ERA uses an excellent model and data assimilation system, using many independent, quality checked observations. In fact, Vergados et al (2015) state "ERA-Interim is one of the most advanced global atmospheric models simulating the state of the atmosphere with accuracy similar to what is theoretically possible (Simmons and Hollingsworth, 2002) using a 4D-Var method (Simmons et al, 2005)." 40 (7) Our results show, in general, that the RO observations have smaller errors than the radiosonde errors, in agreement with previous studies.…”