Abstract
Abstract. We construct a 9-year data record (2007–2015) of the tropospheric specific humidity using Global Positioning System radio occultation (GPS RO) observations from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission. This record covers the ±40∘ latitude belt and includes estimates of the zonally averaged monthly mean specific humidity from 700 up to 400 hPa. It includes three major climate zones: (a) the deep tropics (±15∘), (b) the trade winds belts (±15–30∘), and (c) the subtropics (±30–40∘). We find that the RO observations agree very well with the European Centre for Medium-Range Weather Forecasts Re-Analysis Interim (ERA-Interim), the Modern-Era Retrospective Analysis for Research and Applications (MERRA), and the Atmospheric Infrared Sounder (AIRS) by capturing similar magnitudes and patterns of variability in the monthly zonal mean specific humidity and interannual anomaly over annual and interannual timescales. The JPL and UCAR specific humidity climatologies differ by less than 15 % (depending on location and pressure level), primarily due to differences in the retrieved refractivity. In the middle-to-upper troposphere, in all climate zones, JPL is the wettest of all data sets, AIRS is the driest of all data sets, and UCAR, ERA-Interim, and MERRA are in very good agreement, lying between the JPL and AIRS climatologies. In the lower-to-middle troposphere, we present a complex behavior of discrepancies, and we speculate that this might be due to convection and entrainment. Conclusively, the RO observations could potentially be used as a climate variable, but more thorough analysis is required to assess the structural uncertainty between centers and its origin.
Highlights
The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) (Flato et al, 2013) reported that identifying the vertical structure of humidity is subject to great uncertainty, because dynamical processes that cannot be captured by one sensor alone drive water vapor
In the middle-to-upper troposphere, in all climate zones, JPL is the wettest of all data sets, Atmospheric Infrared Sounder (AIRS) is the driest of all data sets, and University Corporation for Atmospheric Research (UCAR), ERA-Interim, and Modern-Era Retrospective Analysis for Research and Applications (MERRA) are in very good agreement, lying between the JPL and AIRS climatologies
We could explain these differences, we cannot speculate which center is closer to the truth; we demonstrate that both JPL and UCAR essentially provide similar specific humidity climatologies within the retrieval uncertainty
Summary
The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) (Flato et al, 2013) reported that identifying the vertical structure of humidity is subject to great uncertainty, because dynamical processes that cannot be captured by one sensor alone drive water vapor. Ground- and space-based platforms, reanalyses, and model simulations do not provide precise knowledge of the water vapor’s concentration, or its trends over time, in multiple regions of the Earth’s atmosphere (Sherwood et al, 2010). This is because of a combination of different reasons that include (a) sampling bias due to cloudiness, deep convection, or surface emissivity variations; (b) biases due to limited local time coverage, or random observations versus volume-filling scans; (c) coarse spatial resolution, and (d) misrepresentation of the planetary boundary layer’s moisture content (Hannay et al, 2009) that induces errors in the lower-to-middle troposphere moist convection. Space-based microwave (MW) limb sounders, despite having low sensitivity to precipitation and clouds, have a coarse vertical reso-
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