Operational assimilation of GPS zenith total delay observations into the met office numerical weather prediction models

Monthly Weather Review

Volumn 140, Issue 8, 2012, Pages 2706-2719

  Bennitt, Gemma V ^a   Jupp, Adrian ^a  

^a MET OFFICE   (United Kingdom)

Author keywords

Numerical weather prediction forecasting; Satellite observations

Indexed keywords

CLOUD FORECASTS; FOUR-DIMENSIONAL VARIATIONAL DATA ASSIMILATION; GPS RECEIVERS; GROUND BASED; NORTH ATLANTIC; NUMERICAL WEATHER PREDICTION; NUMERICAL WEATHER PREDICTION MODELS; NWP MODEL; OPERATIONAL ASSIMILATION; SATELLITE OBSERVATIONS; ZENITH TOTAL DELAYS;

FORECASTING; GLOBAL POSITIONING SYSTEM; THREE DIMENSIONAL COMPUTER GRAPHICS; VALUE ENGINEERING;

THREE DIMENSIONAL;

ACCURACY ASSESSMENT; CLOUD COVER; DATA ASSIMILATION; FOUR-DIMENSIONAL MODELING; GPS; GROUND-BASED MEASUREMENT; NUMERICAL MODEL; OBSERVATIONAL METHOD; RADIOSONDE; RELATIVE HUMIDITY; SATELLITE DATA; THREE-DIMENSIONAL MODELING; WEATHER FORECASTING; ZENITH ANGLE;

EID: 84867510948     PISSN: 00270644     EISSN: 15200493     Source Type: Journal    
DOI: 10.1175/MWR-D-11-00156.1     Document Type: Article

References (32)

1. Bengtsson, L., and Coauthors, 2003: The use of GPS measurements for water vapour determination. Bull. Amer. Meteor. Soc., 84, 1249-1258.
2. Bevis, M., S. Businger, T. Herring, C. Rocken, R. Anthes, and R. Ware, 1992: GPS meteorology: Remote sensing of atmospheric water vapor using the Global Positioning System. J. Geophys. Res., 97, 15 787-15 801.
3. Bevis, M., S. Businger, S. Chiswell, T. Herring, R. Anthes, C. Rocken, and R. Ware, 1994: GPS meteorology: Mapping zenith wet delays onto precipitable water. J. Appl. Meteor., 33, 379-386.
4. Boniface, K., and Coauthors, 2009: Impact of high-resolution data assimilation of GPS zenith delay on Mediterranean heavy rainfall forecasting. Ann. Geophys., 27, 2739-2753.
5. Cady-Pereira, K. E., M. W. Shephard, D. D. Turner, E. Mlawer, S. A. Clough, and T. J. Wagner, 2008: Improved daytime column-integrated precipitable water vapor from Vaisala radiosonde humidity sensors. J. Atmos. Oceanic Technol., 25, 873-883.
6. Courtier, P., C. Freydier, J.-F. Geleyn, F. Rabier, and M. Rochas, 1991: The Arpege project at Meteo France. Proc. ECMWF Seminar on Numerical Methods in Atmospheric Models, Vol. II, Reading, United Kingdom, ECMWF, 192-231.
7. Davies, T., M. J. P. Cullen, A. J. Malcolm, M. H. Mawson, A. Staniforth, A. A. White, and N. Wood, 2005: A new dynamical core for the Met Office's global and regional modelling of the atmosphere. Quart. M. J. J. Roy. Meteor. Soc., 131, 1759-1782.
8. Dee, D. P., 2005: Bias and data assimilation. Quart. J. Roy. Meteor. Soc., 131, 3323-3343.
9. de Haan, S., I. Holleman, and A. A. M. Holtslag, 2009: Real-time water vapor maps from a GPS surface network: Construction, validation, and applications. J. Appl. Meteor. Climatol., 48, 1302-1316.
10. Duan, J., and Coauthors, 1996: GPS meteorology: Direct estimation of the absolute value of precipitable water. J. Appl. Meteor., 35, 830-838.
11. Emardson, T. R., and H. J. P. Derks, 2000: On the relation between the wet delay and the integrated precipitable water vapour in the European atmosphere. Meteor. Appl., 7, 61-68.
12. Faccani, C., R. Ferretia, R. Pacione, T. Paolucci, F. Vespe, and L. Cucurull, 2005: Impact of a high density GPS network on the operational forecast. Adv. Geosci., 2, 73-76.
13. Grell, G. A., K. Dudhia, and D. R. Stauffer, 1995: A description of the fifth-generation Penn State/NCAR Mesoscale Model (MM5). NCAR Tech. Note NCAR/TN-3981STR, 117 pp.
14. Gutman, S. I., S.R. Sahm, S. G. Benjamin, B. E. Schwartz, K. L. Holub, J. Q. Stewart, and T. L. Smith, 2004: Rapid retrieval and assimilation of ground-based GPS precipitable water observations at the NOAA forecast systems laboratory: Impact on weather forecasts. J.Meteor. Soc. Japan, 82, 351-360.
15. Higgins, M., 2001: Progress in 3D-variational assimilation of total zenith delay at the Met Office. Phys. Chem. Earth, 26, 445-449.
16. Jupp, A., 2006: Met Office assimilation results: TOUGH Deliverable Item D48, 35 pp. [Available online at http://web.dmi.dk/pub/tough/deliverables/d48-assimilation-meto.pdf.]
17. Lorenc, A. C., 1986: Analysis methods for numerical weather prediction. Quart. J. Roy. Meteor. Soc., 112, 1177-1194.
18. Lorenc, A. C., and Coauthors, 2000: The Met Office global threedimensional variational data assimilation scheme. Quart. J. Roy. Meteor. Soc., 126, 2991-3012.
19. Macpherson, S. R., G. Deblonde, J. M. Aparicio, and B. Casati, 2008: Impact of NOAA ground-based GPS observations on the Canadian Regional Analysis and Forecast System. Mon. Wea. Rev., 136, 2727-2746.
20. Niell, A. E., 1996: Global mapping functions for the atmospheric delay at radio wavelengths. J. Geophys. Res., 101, 3227-3246.
21. Pacione, R., B. Pace, H. Vedel, S. de Haan, R. Lanotte, and F. Vespe, 2011: Combination methods of tropospheric time series. Adv. Space Res., 47, 323-335.
22. Poli, P., and Coauthors, 2007: Forecast impact studies of zenith total delay data from European near real-time GPS stations in Météo France 4DVAR. J. Geophys. Res., 112, D06114, doi:10.1029/2006JD007430.
23. Rawlins, R., S. P. Ballard, K. J. Bovis, A. M. Clayton, D. M. Li, G.W. Inverarity, A. C. Lorenc, and T. J. Payne, 2007: The Met Office global four-dimensional variational data assimilation scheme. Quart. J. Roy. Meteor. Soc., 133, 347-362.
24. Rennie, M., 2010: The impact of GPS radio occultation assimilation at the Met Office. Quart. J. Roy. Meteor. Soc., 136, 116-131.
25. Rogers, E., T. L. Black, D. G. Deaven, G. J. DiMego, Q. Zhao, M. Baldwin, N. W. Junker, and Y. Lin, 1996: Changes to the operational "early" eta analysis/forecast system at the National Centers for Environmental Prediction. Wea. Forecasting, 11, 391-413.
26. Rueger, J. M., 2002: Refractive index formulae for radio waves. Proc. FIG XXII International Congress, Washington, DC, International Federation of Surveyors, JS28. [Available online at http://www.fig.net/pub/fig_2002/js28/js28_rueger.pdf.]
27. Smith, E. K., and S. Weintraub, 1953: The constants in the equation for atmospheric refractive index at radio frequencies. Proc. IRE, 41, 1035-1037.
28. Thornton, H. E., D. R. Jackson, S. Bekki, N. Bormann, Q. Errera, A. J. Geer, W. A. Lahoz, and S. Rharmili, 2009: The ASSET intercomparison of stratosphere and lower mesosphere humidity analyses. Atmos. Chem. Phys., 9, 995-1016.
29. Turner, D. D., B. M. Lesht, S. A. Clough, J. C. Liljegren, H. E. Revercomb, and D. C. Tobin, 2003: Dry bias and variability in Vaisala RS80-H radiosondes: The ARM experience. J. Atmos. Oceanic Technol., 20, 117-132.
30. Vedel, H., and X.-Y. Huang, 2004: Impact of ground based GPS data on numerical weather prediction. J. Meteor. Soc. Japan, 82, 459-472.
31. Wang, J., and L. Zhang, 2008: Systematic errors in global radiosonde precipitable water data from comparisons with ground-based GPS measurements. J. Climate, 21, 2218-2238.
32. Yan, X., V. Ducrocq, P. Poli, M. Hakam, G. Jaubert, and A. Walpersdorf, 2009: Impact of GPS zenith delay assimilation on convective-scale prediction of Mediterranean heavy rainfall. J. Geophys. Res., 114, D03104, doi:10.1029/2008JD011036.