Impact of Iranian permanent GPS network precipitable water estimates on numerical weather prediction

Document Type : Original Article

Authors

1 Civil Engineering Department, Babol Noshirvani University of Technology, Babol, Mazandaran, Iran

2 Atmospheric Science and Meteorological Research Center, Tehran, Iran

3 I.R. Iran Meteorological Organization, P.O. Box 13185-461, Tehran, Iran

Abstract

The aim of this study is to assess the impact of continuous and precise ground-based GPS water vapor
estimates as a by-product of Iranian Permanent GPS Network (IPGN) geodetic data processing, together
with conventional surface and upper air meteorological data on the short range prediction of rainfall and
surface moisture fields, including 2 m relative humidity and Precipitable Water Vapor (PWV) over north
of Iran. The Weather Research and Forecasting (WRF) model and its Four-Dimentional Variational Data
Assimilation (4DVAR) system is used to determine the impact of data assimilation on simulation of three
heavy rainfall cases that occurred over the northern part of Iran. All three rainfall cases considered in this
study are associated with a shallow and cold high pressure located over Russia that extends towards the
southern Caspian Sea. The results of numerical experiments showed that the assimilation of ground-based
GPS PWV data, on average, improves simulation of precipitation, PWV and near surface relative
humidity, even though the skill declines after 24-h simulation. It is found that inclusion of GPS PWV
improved the predicted accumulated precipitation in day-1 of the model simulations for February and
November cases up to 7 percent while there was almost no positive impact in September case. Results
suggest that incorporation of observations in initial conditions of the WRF gives generally a slight
improvement in 2 m relative humidity forecasts when compared with the control experiment without
assimilation. Assimilation of GPS PWV in February and September cases reduces, on average, 0.8 mm the
Mean Absolute Error (MAE) of the PWV model during 12-h forecast period. Overall, best results in terms
of MAEs were achieved when GPS water vapor estimations were used along with conventional surface
and upper air radiosonde data.

Keywords

References

Barker, D. M., Huang, W., Guo, Y. R., & Xiao, Q. (2004). A three dimensional variational (3DVAR) system with
     MM5: implementation and initial results. Mon. Weather Rev.132:897–914.
Barker, D., Huang, X-Y., Liu, Z., Auligne, T., Zhang, X., Rugg, S., Ajjaji, R., Bourgeois, A., Bray, J., Chen, Y., Demirtas, M., Guo, Y-R., Henderson, T., Huang, W., Lin, H-C., Michalakes, J., Rizvi, S., & Zhang, X. (2012). The weather research and forecasting model's community variational/ensemble data assimilation system: WRFDA. Bulletin of the American Meteorological Society 93: 831-843.
Bauer, H.S., Wulfmeyer, V., Schwitalla, T., Zus, F.,  & Grzeschik, M. (2010). Operational assimilation of GPS slant path delay measurements into the MM5 4DVAR system.Tellus A. 2010 International Meteorological Institute in Stockholm DOI: 10.1111/j.1600-0870.2010.00489.x,
Bevis, M., Businger, S., Herring, T.A., Rocken, C.,  Anthes, R.A., & Ware R.H. (1992). GPS meteorology: remote sensing of the atmospheric water vapor using the global positioning system. J. Geophys. Res., 97(D14):15787–15801.
Bevis, M., Chiswell, S.,  Herring, T.A.,  Anthes, R.A., Rocken, C.,  & Ware, R.H. (1994). GPS meteorology: mapping zenith wet delays onto precipitable water. J. Appl. Meteor.,33:379–386.
Boniface, K., Ducrocq, V., Jaubert, G., Yan, X., Brousseau, P., Masson, F., Champollion, C., Ch´ery, J., & Doerflinger, E. (2009). Impact of high-resolution data assimilation of GPS zenith delay on Mediterranean heavy rainfall forecasting. Annales Geophysicae 27: 2739–2753.
Chen, F., & Dudhia, J. (2001).  Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 Modeling System. II: preliminary model validation. Mon. Weather Rev.129:587–604.
Choy, S., Wang, C., Zhang, K., & Kuleshov, Y. (2013).  GPS sensing of precipitable water vapour during the March 2010 Melbourne storm. Adv. Space Res. 52 (2013) 1688–1699.
Dai, A., Wang, J., Ware, R.H., & Van Hove, T. (2002).  Diurnal variation in water vapor over North America and its implications for sampling errors in radiosonde humidity. J. Geophys. Res. 107, 4090, doi:10.1029/2001JD000642.
Davis, J.L., Herring, T.A., Shapiro, I.I.,  Rogers, A.E.E., & Elgered, G. (1985). Geodesy by radio interferometry: Effects of atmospheric modeling errors on estimates of baseline length. Radio Science, Vol. 20, Issue 6, pages 1593–1607.
Deeter, M.N. (2007). A new satellite retrieval method for precipitable water vapor over land and ocean. Geophys Res Lett 34:L02815. doi:10.1029/2006GL028019.
Dietrich, S.V.R., Johnsen, K.P., Miao, J., & Heygster, G. (2004).  Comparison of tropospheric water vapour over Antarctica derived from AMSUB data, ground-based GPS data and the NCEP/NCAR reanalysis. J Meteorol Soc Jpn 82:259–267.
Divakarla, M.G., Barnet, C.D., Goldberg, M.D., McMillin, L.M., Maddy, E., Wolf, W., Zhou, L., & Liu, X. (2006).  Validation of atmospheric infrared sounder temperature and water vapor retrievals with matched radiosonde measurements and forecasts. J Geophys Res 111:D09S15. doi:10.1029/2005JD006116.
Dong, J., & Xue, M. (2012). Assimilation of radial velocity and reflectivity data from coastal WSR-88D radars  using ensemble Kalman filter for the analysis and forecast of landfalling hurricane Ike (2008).  Q. J. R. Meteorol. Soc., DOI: 10.1002/qj.1970.
Duan, J.P., Bevis, M., & Fang, P. (1996). GPS meteorology: Direct estimation of the absolute value of precipitable water. J. Appl. Meteor., 35, 830–838.
Dudhia, J. (1989). Numerical study of convection observed during the winter monsoon experiment using a
mesoscale two-dimensional model. J. Atmos. Sci. 46:3077–3107.
Emardson, T.R., Simons, M., & Webb, F.H. (2003). Neutral atmospheric delay in interferometric synthetic aperture radar applications: statistical description and mitigation. J. Geophys. Res.  108(B5): 2231. doi:10.1029/2002JB001781.
Falvey, M., & Beavan, J. (2002).  The impact of GPS precipitable water assimilation on mesoscale model retrievals of orographic rainfall during SALPEX’96. Mon. Weather Rev.130:2874–2888.
Fischer, C., Montmerle, T., Berre, L., Auger, L. & Stefanescu, S. E. (2006). An overview of the variational assimilation in the ALADIN/ FRANCE NWP system. Q. J. R. Meteorol. Soc., 131, 3477–3492.
Foster, J., Bevis, M., Chen, Y.L., Businger, S., & Zhang, Y. (2003). The Ka‘storm (November 2000): imaging precipitable water using GPS. J Geophys Res Atmos (1984–2012) 108(D18):4585. doi:10.1029/2003JD003413.
Gauthier, P., Tanguay, M., Laroche, S., &  Pellerin, S. (2007).  Extension of 3DVAR to 4DVAR: Implementation of 4DVAR at the Meteorological Service of Canada. Mon. Wea. Rev., 135, 2339– 2364.
Govindankutty, M., & Chandrasekar, A. (2011). Impact of assimilation of ATOVS temperature and humidity and SSM/I total precipitable water on the simulation of a monsoon depression. Natural Hazards 59:1647–1669 DOI 10.1007/s11069-011-9857-x.
Gradinarsky, L.P., Johansson, J.M., Bouma, H.R., Scherneck, H.G., & Elgered, G. (2002). Climate monitoring using GPS, Phys. Chem. Earth, 27, 225{340, doi:10.1016/S1474-7065(02)00009-8.
Guerova, G., Bettems, J.M., Brockmann, E., & Matzler, C.H. (2004). Assimilation of the GPS-derived integrated water vapour (IWV) in the MeteoSwiss numerical weather prediction model – a first experiment. Phys. Chem. Earth, 29: 177–186.
Guerova, G., Jones, J., Douša, J., Dick, G., de Haan, S., Pottiaux, E., Bock, O., Pacione, R., Elgered, G., Vedel, H., &  Bender, M. (2016).  Review of the state of the art and future prospects of the ground-based GNSS meteorology in Europe, Atmos. Meas. Tech., 9, 5385-5406, doi:10.5194/amt-9-5385-2016.
Guldner, J., & Spankuch, D. (1999).  Results of year-round remotely sensed integrated water vapor by ground-based microwave radiometry. J. Appl. Meteor.38: 981–988.
Guo, Y.R., Kusaka, H., Barker, D.M., Kuo, Y.H., & Crook, A. (2004). Assimilation of ground-based GPS PWV with 3DVAR system for a IHOP case. Proc. Of 20th conference on weather analysis and forecast / 16th conference on numerical weather prediction. 11-15 January , Seattle, WA. P1.13.
Gutman, S.I., & Benjamin, S.G. (2001). The Role of Ground-Based GPS Meteorological Observations in Numerical Weather Prediction, GPS Solut, Volume 4, No. 4, pp. 16-24.
Ha, S.Y., Kuo, Y.H., Lim, G.H. (2003). Assimilation of GPS slant wet delay: Impact of observing network design.International Workshop on GPS Meteorology, Tsukuba, Japan,  J. Meteorol. Soc. Japan.
Higgins, M. (2001). Progress in 3D-variational assimilation of total zenith delay at the Met Office. Phys. Chem. Earth, 26(6–8): 445–449.
Honda, Y.,Nishijima, M., Koizumi, K., Ohta, Y., Tamiya, K., Kawabata, T., & Tsuyuki, T. (2005).A pre-operational variational data assimilation system for a non-hydrostatic model at the Japan Meteorological Agency: Formulation and preliminary results. Q. J. R. Meteorol. Soc., 131, 3465–3475.
Hong, S.Y., Dudhia, J., & Chen, S.H. (2004). A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon. Weather Rev. 132, 103–120.
Hong, S.Y., Noh, Y., & Dudhia, J. (2006). A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Weather Rev., 134, 2318–2341.
Huang, W., Henderson, T., Bray, J., Chen, Y., Ma, Z.,  Dudhia, J., Guo, Y., Zhang, X.,  Won, D.J.,  Lin, H.C., & Kuo, Y.H. (2008). Four-dimensional variational data assimilation for WRF: formulation and preliminary results. Submitted to Mon. Weather Rev.
Ide, K., Courtier, P., Ghil, M., & Lorenc, A.C. (1997).  Unified notation for data assimilation: operational, sequential and variational. J. Meteorol. Soc. Japan 75:181–189.
Iwabuchi, T., Guo, Y.R., Rocken, C., Van Hove, T., & Kuo, Y.H. (2005). Impact of Ground-based GPS retrievals on moisture field and rainfall forecast in WRF/3DVAR. WRF/MM5 Users’ Workshop- June.
Jadidi, A., Walpersdorf, A., Nankali, H., Aghamohamadi, A., Tavakoli, F., & Djamur, Y. (2006). Sterategy of Iranaian Permanent GPS Network, Geomatics 85 Conference (NCC) Iran.
Kain, J.S. (2004). The Kain–Fritsch convective parameterization: An update. J. Appl. Meteor., 43, 170–181.
Kalnay, E. (2003). Atmospheric modeling, data assimilation and predictability. Published Cambridge University Press, Cambridge, p 364.
Kuo, Y.H., Guo, Y.R., & Westwater, E.R. (1993). Assimilation of precipitable water measurements into a mesoscale numerical model. Mon. Weather Rev., 121, 1215-1238, DOI: 10.1175/15200493.
Kuo, Y.H., Zou, X., & Guo, Y.R. (1996).  Variational assimilation of precipitable water using a nonhydrostatic mesoscale adjoint model. Part I: Moisture retrieval and sensitivity experiments. Mon. Weather Rev., 124, 122-147, DOI: 10.1175.
Leiming, M., Wuyun, Q.,  Geng, F.,  & Zhou, G. (2012). Numerical weather prediction in Yangtze River Delta region with assimilation of AWS and GPS/PWV data. Robotics and Applications (ISRA), 2012 IEEE Symposium on . DOI: 10.1109/ISRA.2012.6219297.
Li, G., & Deng, J. (2013). Atmospheric water monitoring by using ground based GPS during heavy rains produced by TPV and SWV. Adv Meteorol 2013, Article ID 793957. doi:10.1155/2013/793957.
Li, Z., Muller, J.P., & Cross, P. (2003). Comparison of precipitable water vapor derived from radiosonde, GPS, and moderate-resolution imaging spectroradiometer measurements. J Geophys Res 108(D20):4651. doi:10.1029/2003JD003372.
Liou, Y.A., & Huang, C.Y. (2000). GPS observations of PW during the passage of a typhoon. Earth Planets Space 52, 709–712.
Lipton, A.E., Modica, G.D.,  Heckman, S.T., & Jackson A.J. (1995). Satellite-model coupled analysis of convective potential in Florida with VAS water vapor and surface temperature data. Mon. Weather Rev.123:3292–3304.
Mazany, A., Businger, S.,   Gutman, S.I.,  & Roeder, W. (2002). A lightning prediction index that utilizes GPS integrated precipitable water vapor. Weather Forecast 17(5):1034–1047.
Mlawer, E.J., Taubman, S.J., Brown, P.D.,  Iacono, M.J., & Clough, S.A. (1997). Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res. 102(D14):16663–16682.
Monin, A.S., & Obukhov, A.M. (1954). Basic laws of turbulent mixing in the surface layer of the atmosphere. Contributions of the Geophysical  Institute of the Slovak Academy of Sciences, vol. 24, no. 151, pp. 163–187.
Nilsson, T., & Elgered, G. (2008). Long-term trends in the atmospheric water vapor content estimated from ground-based GPS data, J. Geophys. Res., 113, D19101, doi:10. 1029/2008JD010110.
Ohtani, R., & Naito, I. (2000). Comparison of GPS-derived precipitable water vapors with radiosonde observations in Japan. J Geophys Res. 105:26917–26929.
Ortiz de Galisteo, J. P., Toledano, C., Cachorro, V., & Torres, B. (2010).  Improvement in PWV estimation from GPS due to the absolute calibration of antenna phase center variations, GPS Solut., 14, 389–395, doi:10.1007/s10291-010-0163-y.
Pottiaux, E., & Warnant, R. (2002). First comparisons of precipitable water vapor estimation using GPS and water vapor radiometers at the Royal Observatory of Belgium. GPS Solut 6(1-2):11-17.
Pramualsakdikul, S., Haas, R., Elgered, G., & Scherneck, H.G. (2007). Sensing of diurnal and semi-diurnal variability in the watervapour content in the tropics using GPS measurements. Meteorol Appl 14:403-412. Doi:10.1002/met.39.
Prasad, A.K.,  & Singh, R.P. (2009). Validation of MODIS Terra, AIRS, NCEP/DOE AMIP-II Reanalysis-2, and AERONET Sun photometer derived integrated precipitable water vapor using ground-based GPS receivers over India, J.. Geophys. Res, 114, D05107, doi:10.1029/2008JD011230.
Rabier, F.,  Ja rvinen, H., Klinker, E., Mahfouf, J.F., & Simmons, A. (2000). The ECMWF operational implementation of four dimensional variational assimilation. Q. J. R. Meteorol. Soc., 126, 1143–1170.
Rocken, C., Ware, R.,  Van Hove, T., Solheim, F., Alber, C., & Johnson, J. (1993). Sensing Atmospheric Water Vapor with the Global Positioning System, Geophys. Res. Lett.., 20, 2631-2634.
Rocken, C., Van Hove, T., & Ware, R. (1997). Near real-time sensing of atmospheric water vapor. Geophys. Res. Lett.., 24, 3221–3224.
Rüeger, J.M. (2002).  Refractive index formula for radio waves. Integration of techniques and corrections to achieve accurate engineering. Proceedings of the XXII FIG Intional Congress ACSM/SPRS Annual Conference, Washington, DC, USA, 19–26.
Saastamoinen, J. (1972).  Contributions to the theory of atmospheric refraction. Bull. Geodesique 105, 13–34.
Saito, K., Ishida, J., Aranami, K., Hara, T., & Segawa, T. (2007). Nonhydrostatic atmospheric models and operational development at JMA. J. Meteorol. Soc. Japan 85B, 271–304.
Sharifi, M.A., Azadi, M., & Sam Khaniani, A. (2016). Numerical simulation of rainfall with assimilation of conventional and GPS observations over north of Iran, Annals of Geophysics. Volume 59, Issue 3.
Sibylle, V., Dietrich, R., Rulke, A., Fritsche, M., Steigenberger, P., & Rothacher, M. (2010). Validation of precipitable water vapor within the NCEP/DOE reanalysis using global GPS observations from one decade. J Clim 23:1675–1695. doi:10.1175/ 2009JCLI2787.1.
Skamarock, W.C., Klemp, J., Dudhia, J., Gill, D., Barker, D., Duda, M., Hwang, X.Y., & Powers, J. (2008). A Description of the Advanced Research WRF Version 3, NCAR Tech Note NCAR/TN-4751STR, UCAR Communications, Boulder, CO, 125 pp.
Tregoning, P., Boers, R.,  O’Brien, D., & Hendy, M. (1998). Accuracy of absolute precipitable water vapour estimates from GPS, J. Geophys. Res., 103(D22), 28,701–28,710.
Van Baelen, J.,  Aubagnac, J.P., & Dabas, A. (2005). Comparison of Near–Real time estimates of integrated water vapor derived with GPS, radiosondes, and microwave radiometer. J. Atmos. Oceanic Technol. 22, 201–210.
Wang, Y., Liu, Y., Liu, L., Guo, Z., Ge, X., & Xu, H. (2009). Retrieval of the change of precipitable water vapor with zenith tropospheric delay in the Chinese mainland. Adv. Space Res. 43 (2009) 82–88.
Wu, P., Hamada, J.,  Mori, S., Tauhid, Y.I.,  Yamanaka, M.D., & Kimura, F. (2003). Diurnal variation of precipitable water over a mountainous area of Sumatra Island. J. Appl. Meteorol., 42, pp. 1107–1115 http://dx.doi.org/10.1175/1520-0450(2003)042<1107:DVOPWO>2.0.CO;2.
Yunck, T.P., Liu, C.H., & Ware, R. (2002). A history of GPS sounding. Terr Atmos Ocean Sci 11:1–20.
Zhang, M., Ni, Y., & Zhan, F. (2007). Variational assimilation of GPS precipitable water vapor and hourly rainfall observations for a meso- β-scale heavy precipitation event during the 2002 Mei-Yu season. Adv. Atmos. Sci. 24, 509–526.
Earth Observation and Geomatics Engineering
Volume 1, Issue 2 - Serial Number 2
December 2017
Pages 100-111

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