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

To precisely and conveniently estimate zenith tropospheric delay (ZTD), troposphere refractivity is deduced through global pressure and temperature 2w (GPT2w) model and surface meteorology devices, ZTD is estimated based on integration of refractivity in the zenith direction. When surface meteorological measurements are absent, all parameters including surface meteorology and lapse rate are estimated by GPT2w. Validation is carried out using observed data in the year 2012 at 8 international GNSS service (IGS) stations. Results indicate that when surface meteorological parameters are available, the annual accuracy is improved by 27% than Saastamoinen model. Meanwhile, annual bias of the other scheme is decreased by 21% than the GPT2w+Saastamoinen model. For most stations, the bias shows seasonal characteristics, high elevation, high longitude and low latitude can bring less bias.

Estimating Zenith Tropospheric Delay Based on GPT2w Model