{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T13:33:16Z","timestamp":1768483996899,"version":"3.49.0"},"reference-count":55,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2020,12,30]],"date-time":"2020-12-30T00:00:00Z","timestamp":1609286400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100006245","name":"Ministry of Science and Technology, Israel","doi-asserted-by":"publisher","award":["3-14814"],"award-info":[{"award-number":["3-14814"]}],"id":[{"id":"10.13039\/501100006245","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Improving the accuracy of numerical weather predictions remains a challenging task. The absence of sufficiently detailed temporal and spatial real-time in-situ measurements poses a critical gap regarding the proper representation of atmospheric moisture fields, such as water vapor distribution, which are highly imperative for improving weather predictions accuracy. The estimated amount of the total vertically integrated water vapor (IWV), which can be derived from the attenuation of global positioning systems (GPS) signals, can support various atmospheric models at global, regional, and local scales. Currently, several existing atmospheric numerical models can estimate the IWV amount. However, they do not provide accurate results compared with in-situ measurements such as radiosondes. Here, we present a new strategy for assimilating 2D IWV regional maps estimations, derived from combined GPS and METEOSAT satellite imagery data, to improve Weather Research and Forecast (WRF) model predictions accuracy in Israel and surrounding areas. As opposed to previous studies, which used point measurements of IWV in the assimilation procedure, in the current study, we assimilate quasi-continuous 2D GPS IWV maps, combined with METEOSAT-11 data. Using the suggested methodology, our results indicate an improvement of more than 30% in the root mean square error (RMSE) of WRF forecasts after assimilation relative standalone WRF, when both are compared to the radiosonde measured data near the Mediterranean coast. Moreover, significant improvements along the Jordan Rift Valley and Dead Sea Valley areas are obtained when compared to 2D IWV regional maps estimations. Improvements in these areas suggest the impact of the assimilated high resolution IWV maps, with initialization times which coincide with the Mediterranean Sea Breeze propagation from the coastline to highland stations, as the distance to the Mediterranean Sea shore, along with other features, dictates its arrival times.<\/jats:p>","DOI":"10.3390\/rs13010096","type":"journal-article","created":{"date-parts":[[2020,12,30]],"date-time":"2020-12-30T20:13:41Z","timestamp":1609359221000},"page":"96","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["On the Potential of Improving WRF Model Forecasts by Assimilation of High-Resolution GPS-Derived Water-Vapor Maps Augmented with METEOSAT-11 Data"],"prefix":"10.3390","volume":"13","author":[{"given":"Anton","family":"Leontiev","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, Ariel University, Ariel 40700, Israel"}]},{"given":"Dorita","family":"Rostkier-Edelstein","sequence":"additional","affiliation":[{"name":"Department of Environmental Physics, IIBR, Ness-Zyiona 74100, Israel"},{"name":"The Fredy and Nadine Herrmann Institute of Earth Sciences, The Hebrew University of Jerusalem, Rehovot 7610001, Israel"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8902-5540","authenticated-orcid":false,"given":"Yuval","family":"Reuveni","sequence":"additional","affiliation":[{"name":"Department of Physics, Ariel University, Ariel 40700, Israel"},{"name":"Eastern R&amp;D Center, Ariel 40700, Israel"},{"name":"School of Sustainability, Interdisciplinary Center (IDC) Herzliya, Herzliya 4610101, Israel"}]}],"member":"1968","published-online":{"date-parts":[[2020,12,30]]},"reference":[{"key":"ref_1","unstructured":"Maccarthy, J.J., Canziani, O.F., and Leary, N.A. (2001). Atmospheric chemistry and greenhouse gases. Climate Change 2001: Impacts, Adaptation and Vulnerability, Cambridge University Press."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1175\/1520-0450(1994)033<0379:GMMZWD>2.0.CO;2","article-title":"GPS Meteorology: Mapping Zenith Wet Delays onto Precipitable Water","volume":"33","author":"Bevis","year":"1994","journal-title":"J. Appl. Meteorol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"15787","DOI":"10.1029\/92JD01517","article-title":"GPS meteorology: Remote sensing of atmospheric water vapor using the global positioning system","volume":"97","author":"Bevis","year":"1992","journal-title":"J. Geophys. Res."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1175\/1525-7541(2002)003<0149:WVTADO>2.0.CO;2","article-title":"Water Vapor Tracers as Diagnostics of the Regional Hydrologic Cycle","volume":"3","author":"Bosilovich","year":"2002","journal-title":"J. Hydrometeor."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"3104","DOI":"10.1029\/2008JD011036","article-title":"Impact of GPS zenith delay assimilation on convective-scale prediction of Mediterranean heavy rainfall","volume":"114","author":"Yan","year":"2009","journal-title":"J. Geophys. Res. Space Phys."},{"key":"ref_6","unstructured":"Skamarock, W.C., Klemp, B.J., Dudhia, J., Gill, D.O., Barker, D.M., Duda, M.G., Huang, X.-Y., Wang, W., and Powers, J.G. (2008). A Description of the Advanced Research WRF Version 3, National Center for Atmospheric Research. NCAR Tech. Note, NCAR\/TN-468+STR."},{"key":"ref_7","unstructured":"Skamarock, W.C., Klemp, J.B., Dudhia, J., Gill, D.O., Liu, Z., Berner, J., Wang, W., Powers, J.G., Duda, M.G., and Barker, D.M. (2019). A Description of the Advanced Research WRF Version 4, National Center for Atmospheric Research. No. NCAR\/TN-556+STR, NCAR Technical Note."},{"key":"ref_8","unstructured":"Kley, D., Stone, E., and Henderson, W. (2000). SPARC Assessment of Upper Tropospheric and Stratospheric Water Vapor, World Clim. Res. Program. WCRP 113, WMO\/TD-1043, SPARC Rep. 2."},{"key":"ref_9","first-page":"D09S10","article-title":"Absolute accuracy of water vapor measurements from six operational radiosonde types launched during AWEX-G and implications for AIRS validation","volume":"111","author":"Miloshevich","year":"2006","journal-title":"J. Geophys. Res."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Soden, B., Turner, D.D., Lesht, B.M., and Miloshevich, L.M. (2004). An analysis of satellite, radiosonde, and lidar observations of upper tropospheric water vapor from the Atmospheric Radiation Measurement Program. J. Geophys. Res. Space Phys., 109.","DOI":"10.1029\/2003JD003828"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"7857","DOI":"10.1029\/2000JD900837","article-title":"Climatological characteristics of the tropical tropopause as revealed by radiosondes","volume":"106","author":"Seidel","year":"2001","journal-title":"J. Geophys. Res."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1029\/2009EO180001","article-title":"Geodesy in the 21st Century","volume":"90","author":"Wdowinski","year":"2009","journal-title":"Eos"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"830","DOI":"10.1175\/1520-0450(1996)035<0830:GMDEOT>2.0.CO;2","article-title":"GPS Meteorology: Direct Estimation of the Absolute Value of Precipitable Water","volume":"35","author":"Duan","year":"1996","journal-title":"J. Appl. Meteorol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"803","DOI":"10.1029\/RS009i010p00803","article-title":"An improved equation for the radio refractive index of air","volume":"9","author":"Thayer","year":"1974","journal-title":"Radio Sci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1867","DOI":"10.1175\/BAMS-D-14-00095.1","article-title":"National Weather Service Forecasters Use GPS Precipitable Water Vapor for Enhanced Situational Awareness during the Southern California Summer Monsoon","volume":"96","author":"Moore","year":"2015","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_16","unstructured":"Shangguan, M., Heise, S., Bender, M., and Dick, G. (2020, January 06). Validation of GPS Atmospheric Water Vapor with WVR Data in Satellite Tracking Mode, 2015. Available online: http:\/\/eprints.uni-kiel.de\/26354\/."},{"key":"ref_17","unstructured":"Heise, S., Dick, G., Gendt, G., and Schmidt, T. (2020, September 15). Integrated Water Vapor from IGS Ground-Based GPS Observations: Initial Results from a Global 5-min Data Set. Available online: http:\/\/gfzpublic.gfz-potsdam.de\/pubman\/item\/escidoc:239433:1\/component\/escidoc:239432\/13798.pdf."},{"key":"ref_18","first-page":"4090","article-title":"Diurnal variation in water vapor over North America and its implications for sampling errors in radiosonde humidity","volume":"107","author":"Dai","year":"2002","journal-title":"J. Geophys. Res."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"26917","DOI":"10.1029\/2000JD900362","article-title":"Comparisons of GPS-derived precipitable water vapors with radiosonde observations in Japan","volume":"105","author":"Ohtani","year":"2000","journal-title":"J. Geophys. Res. Space Phys."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1175\/1520-0450(2001)040<0005:COPWOI>2.0.CO;2","article-title":"Comparison of precipitable water observations in the near tropics by GPS, microwave radiometer, and radiosondes","volume":"40","author":"Liou","year":"2001","journal-title":"J. Appl. Meteorol."},{"key":"ref_21","first-page":"214","article-title":"Validation of MODIS integrated water vapor product against reference GPS data at the Iberian Peninsula","volume":"63","author":"Cachorro","year":"2017","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2011","DOI":"10.1002\/qj.185","article-title":"Comparison of ground-based GPS precipitable water vapour to independent observations and NWP model reanalyses over Africa","volume":"133","author":"Bock","year":"2007","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1007\/s11434-006-0607-5","article-title":"3D water-vapor tomography with Shanghai GPS network to improve forecasted moisture field","volume":"51","author":"Song","year":"2006","journal-title":"Chin. Sci. Bull."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"361","DOI":"10.2151\/jmsj.2004.361","article-title":"Near Real Time GPS Water Vapor Monitoring for Numerical Weather Prediction in Germany","volume":"82","author":"Gendt","year":"2004","journal-title":"J. Meteorol. Soc. Jpn."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2914","DOI":"10.1175\/MWR3436.1","article-title":"Short-Range Forecast Impact from Assimilation of GPS-IPW Observations into the Rapid Update Cycle","volume":"135","author":"Benjamin","year":"2007","journal-title":"Mon. Weather Rev."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"755","DOI":"10.1007\/s00704-016-1894-7","article-title":"Impact of single-point GPS integrated water vapor estimates on short-range WRF model forecasts over southern India","volume":"130","author":"Kumar","year":"2016","journal-title":"Theor. Appl. Clim."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1080\/22797254.2019.1642799","article-title":"Effect of the ingestion in the WRF model of different Sentinel-derived and GNSS-derived products: Analysis of the forecasts of a high impact weather event","volume":"52","author":"Lagasio","year":"2019","journal-title":"Eur. J. Remote Sens."},{"key":"ref_28","unstructured":"Velden, C.S., Hayden, C.M., Nieman, S.J., Menzel, W.P., Wanzong, S., and Goerss, J.S. (2020, June 20). Upper-Tropospheric Winds Derived from Geostationary Satellite Water Vapor Observations, Available online: http:\/\/ntrs.nasa.gov\/search.jsp?R=19980018993."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1125","DOI":"10.1080\/014311699212885","article-title":"Estimating surface air temperatures, from Meteosat land surface temperatures, using an empirical solar zenith angle model","volume":"20","author":"Cresswell","year":"1999","journal-title":"Int. J. Remote. Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"D14105","DOI":"10.1029\/2011JD017237","article-title":"Evaluation of cloud and water vapor simulations in CMIP5 climate models using NASA \u201cA-Train\u201d satellite observations","volume":"117","author":"Jiang","year":"2012","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"537","DOI":"10.5194\/amt-10-537-2017","article-title":"Combining Meteosat-10 satellite image data with GPS tropospheric path delays to estimate regional integrated water vapor (IWV) distribution","volume":"10","author":"Leontiev","year":"2017","journal-title":"Atmos. Meas. Tech."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"14785","DOI":"10.1038\/s41598-018-33163-x","article-title":"Augmenting GPS IWV estimations using spatio-temporal cloud distribution extracted from satellite data","volume":"8","author":"Leontiev","year":"2018","journal-title":"Sci. Rep."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"B02406","DOI":"10.1029\/2005JB003629","article-title":"Troposphere mapping functions for GPS and very long baseline interferometry from European Centre for Medium-Range Weather Forecasts operational analysis data","volume":"111","author":"Boehm","year":"2006","journal-title":"J. Geophys. Res. Solid Earth"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2106","DOI":"10.1093\/gji\/ggv253","article-title":"Calibrating interferometric synthetic aperture radar (InSAR) images with regional GPS network atmosphere models","volume":"202","author":"Reuveni","year":"2015","journal-title":"Geophys. J. Int."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1269","DOI":"10.1093\/gji\/ggu208","article-title":"Analyzing slip events along the Cascadia margin using an improved subdaily GPS analysis strategy","volume":"198","author":"Reuveni","year":"2014","journal-title":"Geophys. J. Int."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Reuveni, Y., Kedar, S., Owen, S.E., Moore, A.W., and Webb, F.H. (2012). Improving sub-daily strain estimates using GPS measurements. Geophys. Res. Lett., 39.","DOI":"10.1029\/2012GL051927"},{"key":"ref_37","unstructured":"Gaete, K., Carrasco, J., Ja\u00f1a, R., and Sep\u00falveda, H. (2020, July 06). A Sensitivity Analysis of the WRF Model in Climate Simulation for an Area in Fuego-Patagonia. Available online: https:\/\/www.researchgate.net\/publication\/335172852_A_sensitivity_analysis_of_the_WRF_model_in_climate_simulation_for_an_area_in_Fuego-Patagonia."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Khain, A., and Pinsky, M. (2018). Physical Processes in Clouds and Cloud Modeling, Cambridge University Press.","DOI":"10.1017\/9781139049481"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1175\/MWR-2840.1","article-title":"Spectral (Bin) Microphysics Coupled with a Mesoscale Model (MM5). Part I: Model Description and First Results","volume":"133","author":"Lynn","year":"2005","journal-title":"Mon. Weather Rev."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2654","DOI":"10.1175\/JAS-D-13-0252.1","article-title":"Evaluation of Precipitating Hydrometeor Parameterizations in a Single-Moment Bulk Microphysics Scheme for Deep Convective Systems over the Tropical Central Pacific","volume":"71","author":"Roh","year":"2014","journal-title":"J. Atmos. Sci."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"3077","DOI":"10.1175\/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2","article-title":"Numerical Study of Convection Observed during the Winter Monsoon Experiment Using a Mesoscale Two-Dimensional Model","volume":"46","author":"Dudhia","year":"1989","journal-title":"J. Atmos. Sci."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"16663","DOI":"10.1029\/97JD00237","article-title":"Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave","volume":"102","author":"Mlawer","year":"1997","journal-title":"J. Geophys. Res. Space Phys."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2318","DOI":"10.1175\/MWR3199.1","article-title":"A New Vertical Diffusion Package with an Explicit Treatment of Entrainment Processes","volume":"134","author":"Hong","year":"2006","journal-title":"Mon. Weather Rev."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"808","DOI":"10.1016\/j.apenergy.2015.10.145","article-title":"An improved multi-step forecasting model based on WRF ensembles and creative fuzzy systems for wind speed","volume":"162","author":"Zhao","year":"2016","journal-title":"Appl. Energy"},{"key":"ref_45","unstructured":"Fisher, M. (2003, January 8\u201312). Background error covariance modelling. Proceedings of the ECMWF Seminar on Recent Development in Data Assimilation for Atmosphere and Ocean, Reading, UK."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1007\/s00376-020-9213-8","article-title":"Impact of Assimilation of Radiosonde and UAV Observations from the Southern Ocean in the Polar WRF Model","volume":"37","author":"Sun","year":"2020","journal-title":"Adv. Atmos. Sci."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Yang, J., Duan, K., Wu, J., Qin, X., Shi, P., Liu, H., Xie, X., Zhang, X., and Sun, J. (2015). Effect of Data Assimilation Using WRF-3DVAR for Heavy Rain Prediction on the Northeastern Edge of the Tibetan Plateau. Adv. Meteorol., 294589.","DOI":"10.1155\/2015\/294589"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Hacker, J., Draper, C., and Madaus, L. (2018). Challenges and Opportunities for Data Assimilation in Mountainous Environments. Atmosphere, 9.","DOI":"10.3390\/atmos9040127"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Hanna, N., Trzcina, E., Moeller, G., Rohm, W., and Weber, R. (2019). Assimilation of GNSS tomography products into WRF using radio occultation data assimilation operator. Atmos. Meas. Tech. Discuss., 1\u201332.","DOI":"10.5194\/amt-2018-419"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"345","DOI":"10.5194\/amt-12-345-2019","article-title":"4DVAR assimilation of GNSS zenith path delays and precipitable water into a numerical weather prediction model WRF","volume":"12","author":"Rohm","year":"2019","journal-title":"Atmos. Meas. Tech."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1175\/1520-0434(1999)014<0137:EOMAEP>2.0.CO;2","article-title":"Evaluation of MM5 and Eta-10 precipitation forecasts over the Pacific Northwest during the cool season","volume":"14","author":"Colle","year":"1999","journal-title":"Weather Forecast."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1301","DOI":"10.1175\/1520-0493(2003)131<1301:AEOTMR>2.0.CO;2","article-title":"An Evaluation of the MM5, RAMS, and Meso-Eta Models at Subkilometer Resolution Using VTMX Field Campaign Data in the Salt Lake Valley","volume":"131","author":"Zhong","year":"2003","journal-title":"Mon. Weather Rev."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1175\/WAF-834.1","article-title":"Evaluation of Real-Time High-Resolution MM5 Predictions over the Great Lakes Region","volume":"20","author":"Zhong","year":"2005","journal-title":"Weather Forecast."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"105307","DOI":"10.1016\/j.atmosres.2020.105307","article-title":"The diurnal variability of precipitable water vapor derived from GPS tropospheric path delays over the Eastern Mediterranean","volume":"249","author":"Ziskin","year":"2021","journal-title":"Atmos. Res."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1016\/j.atmosres.2019.06.012","article-title":"Investigation of sea-breeze\/foehn in the Dead Sea valley employing high resolution WRF and observations","volume":"229","author":"Kunin","year":"2019","journal-title":"Atmos. Res."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/1\/96\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:47:51Z","timestamp":1760179671000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/1\/96"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12,30]]},"references-count":55,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2021,1]]}},"alternative-id":["rs13010096"],"URL":"https:\/\/doi.org\/10.3390\/rs13010096","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,12,30]]}}}