{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T12:36:38Z","timestamp":1769171798864,"version":"3.49.0"},"reference-count":30,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2018,3,10]],"date-time":"2018-03-10T00:00:00Z","timestamp":1520640000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The National Meteorological Satellite Center\/Korean Meteorological Administration (NMSC\/KMA) receives data directly from low Earth orbit (LEO) satellites (including NOAA-18,19; MetOp-A,B; and Suomi-NPP), and generates Level 2 products (e.g., temperature and humidity profile) in near real time. Total precipitable water (TPW) and layer precipitable water (LPW) are also generated using the retrieved humidity profiles. Today, forecasters need meteorologically-significant data fields composited from all available data sources, not multiple maps of observations from individual sources. Hence, TPW and LPW are reproduced using the optimal interpolation (OI) method with numerical weather prediction (NWP) data, in order to generate composite precipitable water (PW) products. In the OI procedure, PW data retrieved from the LEO satellites serve as observation data, while PW data from NWP serve as background data. Error covariances are estimated using a new approach, which considers correlations between observation errors to describe the characteristics of the errors better. Both background and observation error covariance matrices may have non-zero off-diagonal components. The composite PW products are validated using radiosonde data. The validation results for optimally-interpolated LPW (OI LPW) are much better than those for optimally-interpolated TPW (OI TPW). Generally, the OI LPW validation results are better than those for observation and background data; OI LPW data are ~5\u201310% more accurate than background data. Optimally-interpolated PW (OI PW) fields are applied to the correction of NWP forecast fields and the prediction of severe weather.<\/jats:p>","DOI":"10.3390\/rs10030436","type":"journal-article","created":{"date-parts":[[2018,3,12]],"date-time":"2018-03-12T13:13:48Z","timestamp":1520860428000},"page":"436","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Optimal Interpolation of Precipitable Water Using Low Earth Orbit and Numerical Weather Prediction Data"],"prefix":"10.3390","volume":"10","author":[{"given":"Jun-Hyung","family":"Heo","sequence":"first","affiliation":[{"name":"National Meteorological Satellite Center, Korea Meteorological Administration, Jincheon-gun 27803, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Geun-Hyeok","family":"Ryu","sequence":"additional","affiliation":[{"name":"National Meteorological Satellite Center, Korea Meteorological Administration, Jincheon-gun 27803, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jae-Dong","family":"Jang","sequence":"additional","affiliation":[{"name":"National Meteorological Satellite Center, Korea Meteorological Administration, Jincheon-gun 27803, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,3,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"41","DOI":"10.15191\/nwajom.2015.0305","article-title":"A multisensor, blended, layered water vapor product for weather analysis and forecasting","volume":"3","author":"Forsythe","year":"2015","journal-title":"J. Oper. Meteor."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1175\/JTECH1960.1","article-title":"A Blended Satellite Total Precipitable Water Product for Operational Forecasting","volume":"24","author":"Kidder","year":"2007","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1001","DOI":"10.1002\/qj.49711548902","article-title":"Inversion of cloudy satellite sounding radiances by nonlinear optimal estimation. I: Theory and simulation for TOVS","volume":"115","author":"Eyre","year":"1989","journal-title":"Q. J. R. Meteor. Soc."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1248","DOI":"10.1175\/1520-0450(2000)039<1248:GSOTAF>2.0.CO;2","article-title":"Global Soundings of the Atmosphere from ATOVS Measurements: The Algorithm and Validation","volume":"39","author":"Li","year":"2000","journal-title":"J. Appl. Meteor."},{"key":"ref_5","unstructured":"Li, J., Martinez, M.A., Manso, M., Velazquez, M., and Cuevas, G. (2008, January 8\u201312). Physical retrieval algorithm development for operational SEVIRI clear sky nowcasting products. Proceedings of the 2008 EUMETSAT Meteorological Satellite Data User\u2019s Conference, Darmstadt, Germany."},{"key":"ref_6","unstructured":"Gambacorta, A., Barnet, C., Wolf, W., Goldberg, M., King, T., Nalli, N., Maddy, E., Xiong, X., and Divakarla, M. (2012, January 20). The NOAA Unique CrIS\/ATMS Processing System (NUCAPS): Fist Light Results. Proceedings of the ITWG Meeting, Toulouse, France."},{"key":"ref_7","unstructured":"Bouttier, F., and Courtier, P. (2018, March 10). Data assimilation concepts and methods March 1999. Available online: https:\/\/www.ecmwf.int\/sites\/default\/files\/elibrary\/2002\/16928-data-assimilation-concepts-and-methods.pdf."},{"key":"ref_8","unstructured":"Schulz, J., and Lindau, R. (2018, February 24). Towards and Optimal Merging of Satellite Data Sets. Available online: https:\/\/www.researchgate.net\/publication\/228686783."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"3839","DOI":"10.1109\/JSTARS.2017.2723923","article-title":"Improvement of AMSR2 Soil Moisture Products over South Korea","volume":"10","author":"Lee","year":"2017","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_10","first-page":"1783","article-title":"The ECMWF implementation of three-dimensional variational assimilation (3D-Var). Part 1: Formulation","volume":"124","author":"Courtier","year":"1998","journal-title":"Q. J. R. Meteor. Soc."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"111","DOI":"10.3402\/tellusa.v38i2.11707","article-title":"The statistical structure of short-range forecast errors as determined from radiosonde data. Part 1: The wind field","volume":"38","author":"Hollingsworth","year":"1986","journal-title":"Tellus"},{"key":"ref_12","unstructured":"Smith, N., Berndt, E., Zavodsky, B., Pierce, B., Davies, J., Hoese, D., White, K., Frost, G., McKeen, S., and Wheeler, A. (2017, January 27\u201329). The Value of CSPP NUCAPS in Real-Time Applications. Proceedings of the CSPP\/IMAPP Users Group Metting, Madison, WI, USA."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1323","DOI":"10.5194\/amt-8-1323-2015","article-title":"Cross-track Infrared Sounder (CrIS) satellite observations of tropospheric ammonia","volume":"8","author":"Shepard","year":"2015","journal-title":"Atmos. Meas. Technol."},{"key":"ref_14","unstructured":"(2013). Numerical forecasting takes responsibility for the weather and climate industries!\u2013Utilization guide of Numerical Weather Prediction model data for activation of the weather industry. Numerical Modeling Center of the Korea Meteorological Administration. publication report number: 11\u20131360395-000252-01."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/0377-0265(89)90040-7","article-title":"Meteorological Data Assimilation for Oceanographers. Part I: Description and Theoretical Framework","volume":"13","author":"Ghil","year":"1989","journal-title":"Dyn. Atmos. Oceans"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1177","DOI":"10.1002\/qj.49711247414","article-title":"Analysis methods for numerical weather prediction","volume":"112","author":"Lorence","year":"1986","journal-title":"Q. J. R. Meteor. Soc."},{"key":"ref_17","unstructured":"Daley, R. (1991). Atmospheric Data Analysis, Cambridge University Press."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1225","DOI":"10.1175\/1520-0493(1986)114<0861:MOOAAQ>2.0.CO;2","article-title":"Monitoring of observation and analysis quality by a data-assimilation system","volume":"114","author":"Hollingsworth","year":"1986","journal-title":"Mon. Weather Rev."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1747","DOI":"10.1175\/1520-0493(1992)120<1747:TNMCSS>2.0.CO;2","article-title":"The National Meteorological Center\u2019s spectral statistical-interpolation analysis system","volume":"120","author":"Parrish","year":"1992","journal-title":"Mon. Weather Rev."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"181","DOI":"10.2151\/jmsj1965.75.1B_181","article-title":"Unified Notation for Data Assimilation:Operational, Sequential and Variational","volume":"75","author":"Ide","year":"1997","journal-title":"J. Meteor. Soc. Japan"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1029\/RG014i004p00609","article-title":"Retrieval of atmospheric temperature and composition from remote measurements of thermal radiation","volume":"14","author":"Rodgers","year":"1976","journal-title":"Rev. Geophys. Space Phys."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"916","DOI":"10.1364\/AO.38.000916","article-title":"Retrieval of atmospheric profiles from satellite sounder measurements by use of the discrepancy principle","volume":"38","author":"Li","year":"1999","journal-title":"Appl. Opt."},{"key":"ref_23","unstructured":"Martinez, M.A. (2013). Algorithm Theoretical Basis Document for \u201cSEVIRI Physical Retrieval Product\u201d (SPhR-PGE13 v2.0), AEMET."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"809","DOI":"10.1175\/WAF-D-14-00161.1","article-title":"Inverstigation of the Effects of Considering Ballon Drift Information on Radisonde Data Assimilation Using the Four-Dimensional Variational Method","volume":"30","author":"Choi","year":"2015","journal-title":"Weather Forecast."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1759","DOI":"10.1256\/qj.04.101","article-title":"A new dynamical core for the Met Office\u2019s global and regional modeling of the atmosphere","volume":"131","author":"Davies","year":"2015","journal-title":"Q. J. R. Meteor. Soc."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3430","DOI":"10.1175\/JCLI3804.1","article-title":"Impact of balloon drift errors in radiosonde data on climate statistics","volume":"19","author":"McGrath","year":"2006","journal-title":"J. Clim."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"772","DOI":"10.1175\/WAF-D-12-00114.1","article-title":"Impact of radiosonde balloon drift on numerical weather prediction and verification","volume":"28","author":"Laroche","year":"2013","journal-title":"Weather Forecast."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1002\/met.5060020402","article-title":"Radiosonde balloon drift\u2014Does it matter for data assimilation?","volume":"2","author":"MacPherson","year":"1995","journal-title":"Meteor. Appl."},{"key":"ref_29","unstructured":"Martinez, M.A., and Romero, R. (2012). Validation Report for \u201cSEVIRI Physical Retrieval Product\u201d (SPhR-PGE13) v1.2, AEMET."},{"key":"ref_30","unstructured":"Kusselson, S.J., Kidder, S.Q., Forsythe, J.M., Jones, A.S., and Zhao, L. (2009, January 11\u201315). An update on the operational implementation of blended total precipitable water. Proceedings of the 23rd Conference on Hydrology, Phoenix, AZ, USA."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/3\/436\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T14:56:34Z","timestamp":1760194594000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/3\/436"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,3,10]]},"references-count":30,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2018,3]]}},"alternative-id":["rs10030436"],"URL":"https:\/\/doi.org\/10.3390\/rs10030436","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,3,10]]}}}