A global model for the conversion of ZWD to IWV Rózsa, Sz.; Juni I Department of Geodesy and Surveying, Budapest University of Technology and Economics rozsa.szabolcs@epito.bme.hu

Outline Introduction of the models studied; Methodology; Global Models for the Determination of the scale factor ZWD/IWV; Validation with RS observations Conclusion and Outlook

Conversion of ZWD to IWV ZTD is estimated in GNSS processing; ZHD is modeled based on air pressure data (observation/interpolation/model) ZWD = ZTD – ZHD IWV = ZWD × Q

Conversion of ZWD to IWV Usually two approaches (others exist): Bevis et al (1992) expresses the Tm as a linear regression of Ts (North-american RS data) Emardson-Derks (2000) expresses the scale factor as a polynomial function of Ts: (European RS data)

Conversion of ZWD to IWV Similar models exist for different continents, regions These models: usually neglect climatic effects within the studied region are not available globally (places with lack of RS observations) A seamless global model could assist the GNSS based IWV estimation and the validation of the results.

Methodology Global grids of ECMWF ERA-Interim data for the period of 2001-2010 monthly mean solutions (120 data sets) 37 pressure levels Temperature, relative humidity and geopotential 1°×1° resolution Numeric integration to compute Vertical interpolation; ZWD; IWV; Tm (temperature weighted by the water vapour density);

The global TmTs model Approach 1: Estimate the parameters of the TmTs linear regression for each grid point

The global TmTs model The relative difference between the original Bevis et al. and the TmTs model for January, 2001: mean:

The global polynomial model Approach 2: Estimate the model parameters of polynomial Q=f(Ts) with LSA for each grid point.

The global polynomial model

The global polynomial model The relative difference between the original Emardson-Derks polynomial and the global polynomial model for January, 2001: mean: Model artifacts (10%, -10%)

Validation with RS comparisons Altogether 20 globally distributed RS stations period 2010-2016 – independent from the model data used for the derivation ZWD, IWV computed by numerical integration QRS=IWV / ZWD Qmodel=f(TS) – where TS is the surface temperature stemming from RS profiles QRS-Qmodel residuals computed

The RS network RS sites should be available in the NOAA RS database with small gaps tried to have a homogeneous coverage, but still large gaps occur Altogether 58,690 RS profiles were used

Results Hong Kong

Results Curitiba

Results Budapest (HUN)

Results Relative mean bias of Q values (wrt RS observations) Model Bevis 0,7% TmTs 1,3% Emardson-Derks 0,9% Polynomial 0,4%

Conclusion and outlooks Two global models have been derived for the estimation of the scale factor as a function of Ts; Can be used when no RS observations are available in the region for the local fitting of the Q formulae; The global polynomial model provided the smallest global mean bias (0.4%); The improvement was detected mainly in the tropical region; There are some local artifacts mainly in South America, which still need to be investigated; Data sets and software available soon at: http://gpsmet.agt.bme.hu for testing.

Thank You for Your Attention Szabolcs Rózsa, Ildikó Juni Department of Geodesy and Surveying Budapest University of Technology and Economics H-1111 Budapest, Muegyetem rkp. 3 E-mail: rozsa.szabolcs@epito.bme.hu URL: http://www.geod.bme.hu Software and models will be available at http://gpsmet.agt.bme.hu