English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

. We construct a 9-year data record (2007–2015) of the troposphericspecific 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 monthlymean specific humidity from 700 up to 400 hPa. It includes three majorclimate zones: (a) the deep tropics ( ± 15 ∘ ), (b) the trade windsbelts ( ± 15–30 ∘ ), and (c) the subtropics ( ± 30–40 ∘ ).We find that the RO observations agree very well with the European Centre forMedium-Range Weather Forecasts Re-Analysis Interim (ERA-Interim), theModern-Era Retrospective Analysis for Research and Applications (MERRA), andthe Atmospheric Infrared Sounder (AIRS) by capturing similar magnitudes andpatterns of variability in the monthly zonal mean specific humidity andinterannual anomaly over annual and interannual timescales. The JPL and UCARspecific humidity climatologies differ by less than 15 % (depending onlocation and pressure level), primarily due to differences in the retrievedrefractivity. In the middle-to-upper troposphere, in all climate zones, JPLis the wettest of all data sets, AIRS is the driest of all data sets, andUCAR, ERA-Interim, and MERRA are in very good agreement, lying between theJPL and AIRS climatologies. In the lower-to-middle troposphere, we present acomplex behavior of discrepancies, and we speculate that this might be due toconvection and entrainment. Conclusively, the RO observations couldpotentially be used as a climate variable, but more thorough analysis isrequired to assess the structural uncertainty between centers and its origin.

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