{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T19:24:31Z","timestamp":1787340271410,"version":"3.56.0"},"reference-count":19,"publisher":"Society for Industrial & Applied Mathematics (SIAM)","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["SIAM\/ASA J. Uncertainty Quantification"],"published-print":{"date-parts":[[2017,1]]},"abstract":"<jats:p>Following the chaos theory proposed by Lorenz, probabilistic approaches have been widely used in numerical weather prediction. This paper introduces a convection diffusion equation to quantify the dynamic growth of uncertainty for short term forecasts of cloud boundaries. The equation is inserted into a numerical weather prediction model, weather research and forecast. A two parameter model based on wind velocity dispersion and surface evaporation rates parameterizes the stochastically motivated, but deterministic, equation. Prediction verification tests in comparison to observed data show good predictive capability for an hour, with a gradual loss of predictive power continuing for predictions up to three hours shown qualitatively. The methodology can be applied to a variety of topics in numerical weather prediction research.<\/jats:p>","DOI":"10.1137\/16m1092854","type":"journal-article","created":{"date-parts":[[2017,12,6]],"date-time":"2017-12-06T12:21:25Z","timestamp":1512562885000},"page":"1279-1294","source":"Crossref","is-referenced-by-count":2,"title":["A Novel Methodology of Stochastic Short Term Forecasting of Cloud Boundaries"],"prefix":"10.1137","volume":"5","author":[{"given":"Ya-Ting","family":"Huang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James","family":"Glimm","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"351","published-online":{"date-parts":[[2017,12,6]]},"reference":[{"key":"atypb1","first-page":"1024507","author":"Bo W.","year":"2008","journal-title":"Zurich"},{"key":"atypb2","doi-asserted-by":"publisher","DOI":"10.1137\/10079135X"},{"key":"atypb3","doi-asserted-by":"publisher","DOI":"10.1175\/MWR-D-12-00031.1"},{"key":"atypb4","doi-asserted-by":"publisher","DOI":"10.1126\/science.1115255"},{"key":"atypb5","doi-asserted-by":"publisher","DOI":"10.1175\/1520-0434(1993)008<0401:ASTCFS>2.0.CO;2"},{"key":"atypb6","doi-asserted-by":"publisher","DOI":"10.1002\/env.2267"},{"key":"atypb7","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2015.03.001"},{"key":"atypb8","unstructured":"JWGFVR,\n                      Joint Working Group Forecast Verification Research Recommended Methods for Evaluating Cloud and Related Parameters\n                      , Technical report, WWRP 2012-1, World Meteorological Organization, Geneva, Switzerland, 2012."},{"key":"atypb9","first-page":"11790","author":"Kaufman R.","year":"2014","journal-title":"NY"},{"key":"atypb10","first-page":"115","volume":"11","author":"Kaufman R.","year":"2016","journal-title":"S.)"},{"key":"atypb11","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2007.02.014"},{"key":"atypb12","doi-asserted-by":"publisher","DOI":"10.1175\/MWR2949.1"},{"key":"atypb13","doi-asserted-by":"publisher","DOI":"10.1016\/j.cam.2003.09.028"},{"key":"atypb14","doi-asserted-by":"publisher","DOI":"10.1016\/j.solener.2012.04.004"},{"key":"atypb15","unstructured":"L. Pichler, A. Masud, and L. Bergman,\n                      Numerical solution of the Fokker-Planck equation by finite difference and finite element methods - a comparative study\n                      , in Computational Methods in Stochastic Dynamics, V. P. M. Papadrakakis, M. Fragiadakis, ed., Comput. Methods Appl. Sci. 22, Springer, Dordrecht, The Netherlands, 2011, pp. 25-28."},{"key":"atypb16","first-page":"383","author":"She D.","year":"2016","journal-title":"Amsterdam"},{"key":"atypb17","unstructured":"W. C. Skamarock, J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, M. G. Duda, H. X-Y, W. Wang, and J. G. Powers.\n                      A Description of the Advanced Research WRF Version\n                      3, Technical report, NCAR\/TN-475+STR National Center for Atmospheric Research, Boulder, CO, 2008."},{"key":"atypb18","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRS.2012.2232317"},{"key":"atypb19","unstructured":"D. S. Wilks,\n                      Statistical Methods in the Atmospheric Sciences\n                      , Int. Geophys. Ser. 100, Academic Press, Oxford, 2011."}],"container-title":["SIAM\/ASA Journal on Uncertainty Quantification"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/epubs.siam.org\/doi\/pdf\/10.1137\/16M1092854","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T18:27:46Z","timestamp":1787336866000},"score":1,"resource":{"primary":{"URL":"https:\/\/epubs.siam.org\/doi\/10.1137\/16M1092854"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,1]]},"references-count":19,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2017,1]]}},"alternative-id":["10.1137\/16M1092854"],"URL":"https:\/\/doi.org\/10.1137\/16m1092854","relation":{},"ISSN":["2166-2525"],"issn-type":[{"value":"2166-2525","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,1]]}}}