Editorial Type:
Article
Article Type:
Research Article

MOGREPS-UK Convection-Permitting Ensemble Products for Surface Water Flood Forecasting: Rationale and First Results

Brian Golding Met Office, Exeter, United Kingdom

Search for other papers by Brian Golding in
Current site
Google Scholar
PubMed Close
,
Nigel Roberts Met Office@Reading, Reading University, Reading, United Kingdom

Search for other papers by Nigel Roberts in
Current site
Google Scholar
PubMed Close
,
Giovanni Leoncini Met Office@Reading, Reading University, Reading, United Kingdom

Search for other papers by Giovanni Leoncini in
Current site
Google Scholar
PubMed Close
,
Ken Mylne Met Office, Exeter, United Kingdom

Search for other papers by Ken Mylne in
Current site
Google Scholar
PubMed Close
, and
Richard Swinbank Met Office, Exeter, United Kingdom

Search for other papers by Richard Swinbank in
Current site
Google Scholar
PubMed Close
Print Publication:
01 May 2016
DOI:
https://doi.org/10.1175/JHM-D-15-0083.1
Page(s):
1383–1406
Restricted access

ABSTRACT

Flooding is one of the costliest hazards in the United Kingdom. A large part of the annual flood damage is caused by surface water flooding that is a direct result of intense rainfall. Traditional catchment-based approaches to flood prediction are not applicable for surface water floods. However, given sufficiently accurate forecasts of rainfall intensity, with sufficient lead time, actions can be taken to reduce their impact. These actions require reliable information about severity and areas at risk that is clear and easily interpreted. The accuracy requirements, in particular, are very challenging, as they relate to prediction of intensities that occur only infrequently and that typically affect only small areas. In this paper, forecasts of intense rainfall from a new convection-permitting ensemble prediction system are evaluated using radar observations of intense rain and surface water flooding reports. An urban flooding case that occurred in Edinburgh in 2011 is first investigated and then a broader look is taken at performance through a 3-month period during the London Olympic and Paralympic Games in 2012. Conclusions are drawn about the value of the ensemble and the particular means of presenting the forecasts, and areas requiring further work are highlighted.

Current affiliation: Aspen Re, Zurich, Switzerland.

Corresponding author address: Brian Golding, Met Office, FitzRoy Road, Exeter EX1 3PB, United Kingdom. E-mail: brian.golding@metoffice.gov.uk

ABSTRACT

Flooding is one of the costliest hazards in the United Kingdom. A large part of the annual flood damage is caused by surface water flooding that is a direct result of intense rainfall. Traditional catchment-based approaches to flood prediction are not applicable for surface water floods. However, given sufficiently accurate forecasts of rainfall intensity, with sufficient lead time, actions can be taken to reduce their impact. These actions require reliable information about severity and areas at risk that is clear and easily interpreted. The accuracy requirements, in particular, are very challenging, as they relate to prediction of intensities that occur only infrequently and that typically affect only small areas. In this paper, forecasts of intense rainfall from a new convection-permitting ensemble prediction system are evaluated using radar observations of intense rain and surface water flooding reports. An urban flooding case that occurred in Edinburgh in 2011 is first investigated and then a broader look is taken at performance through a 3-month period during the London Olympic and Paralympic Games in 2012. Conclusions are drawn about the value of the ensemble and the particular means of presenting the forecasts, and areas requiring further work are highlighted.

Current affiliation: Aspen Re, Zurich, Switzerland.

Corresponding author address: Brian Golding, Met Office, FitzRoy Road, Exeter EX1 3PB, United Kingdom. E-mail: brian.golding@metoffice.gov.uk
Save
Cover Journal of Hydrometeorology
Journal of Hydrometeorology

  • Baldauf, M., Siefert A. , Förstner J. , Majewski D. , Raschendorfer M. , and Reinhardt T. , 2011: Operational convective-scale numerical weather prediction with the COSMO model: Description and sensitivities. Mon. Wea. Rev., 139, 3887–3905, doi:10.1175/MWR-D-10-05013.1.

    • Search Google Scholar
    • Export Citation

  • Barrett, A. I., Gray S. L. , Kirshbaum D. J. , Roberts N. M. , Schultz D. M. , and Fairman J. G. Jr., 2014: Synoptic versus orographic control on stationary convective banding. Quart. J. Roy. Meteor. Soc., 141, 1101–1113, doi:10.1002/qj.2409.

    • Search Google Scholar
    • Export Citation

  • Bell, H., and Tobin G. , 2007: Efficient and effective? The 100-year flood in the communication and perception of flood risk. Environ. Hazards, 7, 302–311, doi:10.1016/j.envhaz.2007.08.004.

    • Search Google Scholar
    • Export Citation

  • Bowler, N. E., Arribas A. , Mylne K. R. , Robertson K. B. , and Beare S. E. , 2008: The MOGREPS short-range ensemble prediction system. Quart. J. Roy. Meteor. Soc., 134, 703–722, doi:10.1002/qj.234.

    • Search Google Scholar
    • Export Citation

  • Bowler, N. E.,Arribas A. , Beare S. E. , Mylne K. R. , and Shutts G. J. , 2009: The local ETKF and SKEB: Upgrades to the MOGREPS short-range ensemble prediction system. Quart. J. Roy. Meteor. Soc., 135, 767–776, doi:10.1002/qj.394.

    • Search Google Scholar
    • Export Citation

  • Buizza, R., Houtekamer P. L. , Toth Z. , Pellerin G. , Wei M. Z. , and Zhu Y. J. , 2005: A comparison of the ECMWF, MSC, and NCEP global ensemble prediction systems. Mon. Wea. Rev., 133, 1076–1097, doi:10.1175/MWR2905.1.

    • Search Google Scholar
    • Export Citation

  • Burningham, K., Fielding J. , and Thrush D. , 2008: It’ll never happen to me: Understanding public awareness of local flood risk. Disasters, 32, 216–238, doi:10.1111/j.1467-7717.2007.01036.x.

    • Search Google Scholar
    • Export Citation

  • CEH, 2011: UK Hydrological Bulletin January–July 2011. Centre for Ecology and Hydrology, accessed 28 March 2016. [Available online at http://nrfa.ceh.ac.uk/node/110/.]

  • Clark, A. J., Gallus W. A. Jr., Xue M. , and Kong F. , 2009: A comparison of precipitation forecast skill between small convection-permitting and large convection-parameterizing ensembles. Wea. Forecasting, 24, 1121–1140, doi:10.1175/2009WAF2222222.1.

    • Search Google Scholar
    • Export Citation

  • Clark, A. J., and Coauthors, 2011: Probabilistic precipitation forecast skill as a function of ensemble size and spatial scale in a convection-allowing ensemble. Mon. Wea. Rev., 139, 1410–1418, doi:10.1175/2010MWR3624.1.

    • Search Google Scholar
    • Export Citation

  • Clark, A. J., Weiss S. J. , and Kain J. S. , 2012: An overview of the 2010 hazardous weather testbed experimental forecast program spring experiment. Bull. Amer. Meteor. Soc., 93, 55–74, doi:10.1175/BAMS-D-11-00040.1.

    • Search Google Scholar
    • Export Citation

  • Clark, M. R., 2011: An observational study of the exceptional ‘Ottery St Mary’ thunderstorm of 30 October 2008. Meteor. Appl., 18, 137–154, doi:10.1002/met.187.

    • Search Google Scholar
    • Export Citation

  • Davies, T., Cullen M. J. P. , Malcolm A. J. , Mawson M. H. , Staniforth A. , White A. A. , and Wood N. , 2005: A new dynamical core for the Met Office’s global and regional modelling of the atmosphere. Quart. J. Roy. Meteor. Soc., 131, 1759–1782, doi:10.1256/qj.04.101.

    • Search Google Scholar
    • Export Citation

  • Dolan, J. G., and Iadarola S. , 2008: Risk communication formats for low probability events: An exploratory study of patient references. BMC Med. Inf. Decis. Making, 8, 14, doi:10.1186/1472-6947-8-14.

    • Search Google Scholar
    • Export Citation

  • Done, J., Davis C. A. , and Weisman M. L. , 2004: The next generation of NWP: Explicit forecasts of convection using the Weather Research and Forecasting (WRF). Atmos. Sci. Lett., 5, 110–117, doi:10.1002/asl.72.

    • Search Google Scholar
    • Export Citation

  • Duan, Y., and Coauthors, 2012: An overview of Beijing 2008 Olympics Research and Development Project (B08RDP). Bull. Amer. Meteor. Soc., 93, 381–403, doi:10.1175/BAMS-D-11-00115.1.

    • Search Google Scholar
    • Export Citation

  • Edwards, A., Elwyn G. , and Mulley A. , 2002: Explaining risks: Turning numerical data into meaningful pictures. BMJ, 324, 827–830, doi:10.1136/bmj.324.7341.827.

    • Search Google Scholar
    • Export Citation

  • Edwards, J., and Slingo A. , 1996: Studies with a flexible new radiation code. Part I: Choosing a configuration for a large-scale model. Quart. J. Roy. Meteor. Soc., 122, 689–719, doi:10.1002/qj.49712253107.

    • Search Google Scholar
    • Export Citation

  • Essery, R. L. H., Best M. J. , Betts R. A. , Cox P. M. , and Taylor C. M. , 2003: Explicit representation of subgrid heterogeneity in a GCM land surface scheme. J. Hydrometeor., 4, 530–543, doi:10.1175/1525-7541(2003)004<0530:EROSHI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Falconer, R. H., Cobby D. , Smyth P. , Astle G. , Dent J. , and Golding B. , 2009: Pluvial flooding: New approaches in flood warning, mapping and risk management. J. Flood Risk Manage., 2, 198–208, doi:10.1111/j.1753-318X.2009.01034.x.

    • Search Google Scholar
    • Export Citation

  • Faulkner, H., Parker D. , Green C. , and Beven K. , 2007: Developing a translational discourse to communicate uncertainty in flood risk between science and the practitioner. Ambio, 36, 692–704, doi:10.1579/0044-7447(2007)36[692:DATDTC]2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • FFC, 2015: About us. Flood Forecasting Centre, accessed 28 March 2016. [Available online at http://www.ffc-environment-agency.metoffice.gov.uk/about/.]

  • Gebhardt, C., Theis S. E. , Paulat M. , and Ben Bouallegue Z. , 2011: Uncertainties in COSMO-DE precipitation forecasts introduced by model perturbations and variation of lateral boundaries. Atmos. Res., 100, 168–177, doi:10.1016/j.atmosres.2010.12.008.

    • Search Google Scholar
    • Export Citation

  • Germann, U., and Zawadzki I. , 2004: Scale dependence of the predictability of precipitation from continental radar images. Part II: Probability forecasts. J. Appl. Meteor., 43, 74–89, doi:10.1175/1520-0450(2004)043<0074:SDOTPO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Gigerenzer, G., Hertwig R. , van den Broek E. , Fasolo B. , and Katsikopoulos K. V. , 2005: “A 30% chance of rain tomorrow”: How does the public understand probabilistic weather forecasts? Risk Anal., 25, 623–629, doi:10.1111/j.1539-6924.2005.00608.x.

    • Search Google Scholar
    • Export Citation

  • Gill, J., 2008: Communicating forecast uncertainty for service providers. WMO Bull., 57 (4), 237–243.

  • Golding, B. W., Clark P. , and May B. , 2005: The Boscastle flood: Meteorological analysis of the conditions leading to flooding on 16 August 2004. Weather, 60, 230–235, doi:10.1256/wea.71.05.

    • Search Google Scholar
    • Export Citation

  • Golding, B. W., and Coauthors, 2014: Forecasting capabilities for the London 2012 Olympics. Bull. Amer. Meteor. Soc., 95, 883–896, doi:10.1175/BAMS-D-13-00102.1.

    • Search Google Scholar
    • Export Citation

  • Goldman, R., Parker D. , Eaton C. , Borkan J. , Gramling R. , Cover R. , and Ahern D. , 2006: Patients’ perceptions of cholesterol, cardiovascular disease risk, and risk communication strategies. Ann. Fam. Med., 4, 205–212, doi:10.1370/afm.534.

    • Search Google Scholar
    • Export Citation

  • Gregory, D., and Rowntree P. R. , 1990: A mass flux convection scheme with representation of cloud ensemble characteristics and stability-dependent closure. Mon. Wea. Rev., 118, 1483–1506, doi:10.1175/1520-0493(1990)118<1483:AMFCSW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Guha-Sapir, D., Vos F. , Below R. , and Ponserre S. , 2012: Annual disaster statistical review 2011: The numbers and trends. Centre for Research on the Epidemiology of Disasters, 42 pp. [Available online at http://cred.be/sites/default/files/2012.07.05.ADSR_2011.pdf.]

  • Hand, W. H., Fox N. I. , and Collier C. G. , 2004: A study of twentieth-century extreme rainfall events in the United Kingdom with implications for forecasting. Meteor. Appl., 11, 15–31, doi:10.1017/S1350482703001117.

    • Search Google Scholar
    • Export Citation

  • Hanley, K. E., Kirshbaum D. J. , Belcher S. E. , Roberts N. M. , and Leoncini G. , 2011: Ensemble predictability of an isolated mountain thunderstorm in a high-resolution model. Quart. J. Roy. Meteor. Soc., 137, 2124–2137, doi:10.1002/qj.877.

    • Search Google Scholar
    • Export Citation

  • Hanley, K. E., Kirshbaum D. J. , Roberts N. M. , and Leoncini G. , 2013: Sensitivities of a squall line over central Europe in a convective-scale ensemble. Mon. Wea. Rev., 141, 112–133, doi:10.1175/MWR-D-12-00013.1.

    • Search Google Scholar
    • Export Citation

  • Harrison, D., Georgiou S. , Gaussiat N. , and Curtiss A. , 2014: Long-term diagnostics of precipitation estimates and the development of radar hardware monitoring within a radar product data quality management system. Hydrol. Sci. J., 59, 1277–1292, doi:10.1080/02626667.2013.841316.

    • Search Google Scholar
    • Export Citation

  • Hirahara, Y., Ishida J. , and Ishimizu T. , 2012: Trial operation of the local forecast model at JMA. Development of and studies with regional and smaller-scale atmospheric models, regional ensemble, monthly and seasonal forecasting, WMO/WCRP/WGNE Blue Book 2011, World Climate Research Programme, 11–12. [Available online at http://www.wcrp-climate.org/WGNE/BlueBook/2011/chapters/BB_11_S5.pdf.]

  • Hohenegger, C., Walser A. , Langhans W. , and Schaer C. , 2008: Cloud-resolving ensemble simulations of the August 2005 Alpine flood. Quart. J. Roy. Meteor. Soc., 134, 889–904, doi:10.1002/qj.252.

    • Search Google Scholar
    • Export Citation

  • Ikeda, K., Steiner M. , Pinto J. , and Alexander C. , 2013: Evaluation of cold-season precipitation forecasts generated by the hourly updating high-resolution rapid refresh model. Wea. Forecasting, 28, 921–939, doi:10.1175/WAF-D-12-00085.1.

    • Search Google Scholar
    • Export Citation

  • Joslyn, S., and Savelli S. , 2010: Communicating forecast uncertainty: Public perception of weather forecast uncertainty. Meteor. Appl., 17, 180–195, doi:10.1002/met.190.

    • Search Google Scholar
    • Export Citation

  • Joslyn, S., Pak K. , Jones D. , Pyles J. , and Hunt E. , 2007: The effect of probabilistic information on threshold forecasts. Wea. Forecasting, 22, 804–812, doi:10.1175/WAF1020.1.

    • Search Google Scholar
    • Export Citation

  • Joslyn, S., Nadav-Greenberg L. , and Nichols R. M. , 2009: Probability of precipitation: Assessment and enhancement of end-user understanding. Bull. Amer. Meteor. Soc., 90, 185–193, doi:10.1175/2008BAMS2509.1.

    • Search Google Scholar
    • Export Citation

  • Kitchen, M., Brown R. , and Davies A. G. , 1994: Real-time correction of weather radar data for the effects of bright band, range and orographic growth in widespread precipitation. Quart. J. Roy. Meteor. Soc., 120, 1231–1254, doi:10.1002/qj.49712051906.

    • Search Google Scholar
    • Export Citation

  • Kloprogge, P., Van der Sluijs J. , and Wardekker A. , 2007: Uncertainty communication: Issues and good practice. Rep. NWS-E-2007-199, Utrecht University, 60 pp. [Available online at http://www.nusap.net/downloads/reports/uncertainty_communication.pdf.]

  • Knapp, P., Raynor D. , and Berry D. , 2004: Comparison of two methods of presenting risk information to patients about the side effects of medicines. Qual. Saf. Health Care, 13, 176–180, doi:10.1136/qshc.2003.009076.

    • Search Google Scholar
    • Export Citation

  • Kong, F. Y., Droegemeier K. K. , and Hickmon N. L. , 2007: Multiresolution ensemble forecasts of an observed tornadic thunderstorm system. Part II: Storm-scale experiments. Mon. Wea. Rev., 135, 759–782, doi:10.1175/MWR3323.1.

    • Search Google Scholar
    • Export Citation

  • Kunii, M., and Coauthors, 2011: Verifications and intercomparisons of mesoscale ensemble prediction systems in B08RDP. Tellus, 63A, 531–549, doi:10.1111/j.1600-0870.2011.00512.x.

    • Search Google Scholar
    • Export Citation

  • Kurz-Milcke, E., Gigerenzer G. , and Martignn L. , 2008: Transparency in risk communication: Graphical and analogue tools. Ann. N. Y. Acad. Sci., 1128, 18–28, doi:10.1196/annals.1399.004.

    • Search Google Scholar
    • Export Citation

  • Lean, H. W., Clark P. A. , Dixon M. , Roberts N. M. , Fitch A. , Forbes R. , and Halliwell C. , 2008: Characteristics of high-resolution versions of the Met Office Unified Model for forecasting convection over the United Kingdom. Mon. Wea. Rev., 136, 3408–3424, doi:10.1175/2008MWR2332.1.

    • Search Google Scholar
    • Export Citation

  • Lean, H. W., Roberts N. M. , Clark P. A. , and Morcrette C. , 2009: The surprising role of orography in the initiation of an isolated thunderstorm in southern England. Mon. Wea. Rev., 137, 3026–3046, doi:10.1175/2009MWR2743.1.

    • Search Google Scholar
    • Export Citation

  • Leoncini, G., Plant R. S. , Gray S. L. , and Clark P. A. , 2010: Perturbation growth at the convective scale for CSIP IOP18. Quart. J. Roy. Meteor. Soc., 136, 653–670, doi:10.1002/qj.587.

    • Search Google Scholar
    • Export Citation

  • Lock, A. P., 2001: The numerical representation of entrainment in parameterizations of boundary layer turbulent mixing. Mon. Wea. Rev., 129, 1148–1163, doi:10.1175/1520-0493(2001)129<1148:TNROEI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Lock, A. P., Brown A. R. , Bush M. R. , Martin G. M. , and Smith R. N. B. , 2000: A new boundary layer mixing scheme. Part I: Scheme description and single-column model tests. Mon. Wea. Rev., 128, 3187–3199, doi:10.1175/1520-0493(2000)128<3187:ANBLMS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Lorenc, A. C., and Coauthors, 2000: The Met. Office global three-dimensional variational data assimilation scheme. Quart. J. Roy. Meteor. Soc., 126, 2991–3012, doi:10.1002/qj.49712657002.

    • Search Google Scholar
    • Export Citation

  • Molteni, F., Buizza R. , Palmer T. N. , and Petroliagis T. , 1996: The new ECMWF ensemble prediction system: Methodology and validation. Quart. J. Roy. Meteor. Soc., 122, 73–119, doi:10.1002/qj.49712252905.

    • Search Google Scholar
    • Export Citation

  • Moore, R. J., Cole S. J. , Dunn S. , Ghimire S. , Golding B. W. , Pierce C. E. , Roberts N. M. , and Speight L. , 2015: Surface water flood forecasting for urban communities. CREW Rep. CRW2012_03, 33 pp. [Available online at http://www.crew.ac.uk/publications/surface-water-flood-forecasting-urban-communities.]

  • Morss, R. E., Demuth J. L. , and Lazo J. K. , 2008: Communicating uncertainty in weather forecasts: A survey of the U.S. public. Wea. Forecasting, 23, 974–991, doi:10.1175/2008WAF2007088.1.

    • Search Google Scholar
    • Export Citation

  • Murphy, A. H., Lichtenstein S. , Fischhoff B. , and Winkler R. L. , 1980: Misinterpretations of precipitation probability forecasts. Bull. Amer. Meteor. Soc., 61, 695–701, doi:10.1175/1520-0477(1980)061<0695:MOPPF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Paling, J., 2003: Strategies to help patients understand risks. BMJ, 327, 745, doi:10.1136/bmj.327.7417.745.

  • Peachey, J., Schultz D. M. , Morss R. , Roebber P. , and Wood R. , 2013: How forecasts expressing uncertainty are perceived by UK students. Weather, 68, 176–181, doi:10.1002/wea.2094.

    • Search Google Scholar
    • Export Citation

  • Peralta, C., Ben Bouallègue Z. , Theis S. E. , Gebhardt C. , and Buchhold M. , 2012: Accounting for initial condition uncertainties in COSMO-DE-EPS. J. Geophys. Res., 117, D07108, doi:10.1029/2011JD016581.

    • Search Google Scholar
    • Export Citation

  • Peters, P., Bostrom A. , and Cutter S. , 2008: Perspectives on visualizing uncertainty in natural hazards. Risk Assessment, Modeling and Decision Support, A. Bostrom, S. French, and S. Gottlieb, Eds., Risk, Governance and Society, Vol. 14, Springer, 295–318.

  • Pitt, M., 2009: Learning lessons from the 2007 floods. UK Cabinet Office Rep., 462 pp.

  • Price, D., and Coauthors, 2012: Operational use of a grid-based model for flood forecasting. Proc. Inst. Civ. Eng.: Water Manage., 165, 65–77, doi:10.1680/wama.2012.165.2.65.

    • Search Google Scholar
    • Export Citation

  • Price, M., Cameron R. , and Butow P. , 2007: Communicating risk information: The influence of graphical display format on quantitative information perception—Accuracy, comprehension and preferences. Patient Educ. Couns., 69, 121–128, doi:10.1016/j.pec.2007.08.006.

    • Search Google Scholar
    • Export Citation

  • Roberts, N. M., 2000: The relationship between water vapour imagery and thunderstorms. Met Office Forecasting Research Tech. Rep. 110, 40 pp.

  • Roberts, N. M., and Lean H. W. , 2008: Scale-selective verification of rainfall accumulations from high-resolution forecasts of convective events. Mon. Wea. Rev., 136, 78–97, doi:10.1175/2007MWR2123.1.

    • Search Google Scholar
    • Export Citation

  • Roulston, M. S., and Kaplan T. R. , 2009: A laboratory-based study of understanding of uncertainty in 5-day site-specific temperature forecasts. Meteor. Appl., 16, 237–244, doi:10.1002/met.113.

    • Search Google Scholar
    • Export Citation

  • Roulston, M. S., Bolton G. E. , Kleit A. N. , and Sears-Collins A. L. , 2006: A laboratory study of the benefits of including uncertainty information in weather forecasts. Wea. Forecasting, 21, 116–122, doi:10.1175/WAF887.1.

    • Search Google Scholar
    • Export Citation

  • Scheuren, J.-M., le Polain de Waroux O. , Below R. , Guha-Sapir D. , and Ponserre S. , 2008: Annual disaster statistical review: The numbers and trends 2007. Center for Research on the Epidemiology of Disasters Rep., 64 pp. [Available online at http://www.unisdr.org/files/2796_CREDAnnualStatisticalReview2007.pdf.]

  • Schirillo, J., and Stone E. , 2005: The greater ability of graphical versus numerical displays to increase risk avoidance involves a common mechanism. Risk Anal., 25, 555–566, doi:10.1111/j.1539-6924.2005.00624.x.

    • Search Google Scholar
    • Export Citation

  • Seity, Y., Brousseau P. , Malardel S. , Hello G. , Bénard P. , Bouttier F. , Lac C. , and Masson V. , 2011: The AROME-France Convective-Scale Operational Model. Mon. Wea. Rev., 139, 976–991, doi:10.1175/2010MWR3425.1.

    • Search Google Scholar
    • Export Citation

  • Stensrud, D. J., Brooks H. E. , Du J. , Tracton M. S. , and Rogers E. , 1999: Using ensembles for short-range forecasting. Mon. Wea. Rev., 127, 433–446, doi:10.1175/1520-0493(1999)127<0433:UEFSRF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Stephens, E., Mylne K. , and Spiegelhalter D. , 2011: Using an online game to evaluate effective methods of communicating ensemble model output to different audiences. 2011 Fall Meeting, San Francisco, CA, Amer. Geophys. Union, Abstract ED33B-0776.

  • Steppeler, J., Doms G. , Schattler U. , Bitzer H. W. , Gassmann A. , Damrath U. , and Gregoric G. , 2003: Meso-gamma scale forecasts using the nonhydrostatic model LM. Meteor. Atmos. Phys., 82, 75–96, doi:10.1007/s00703-001-0592-9.

    • Search Google Scholar
    • Export Citation

  • Stone, E., Yates J. , and Parker A. , 1997: Effects of numerical and graphical displays on professed risk-taking behaviour. J. Exp. Psychol., 3 (4), 243–256.

    • Search Google Scholar
    • Export Citation

  • Tang, Y., Lean H. W. , and Bornemann J. , 2013: The benefits of the Met Office variable resolution NWP model for forecasting convection. Meteor. Appl., 20, 417–426, doi:10.1002/met.1300.

    • Search Google Scholar
    • Export Citation

  • Tapsell, S., Burton R. , Oakes S. , and Parker D. , 2005: The social performance of flood warning communications technologies. R&D Tech. Summary W5C-016/TS, Environment Agency, 3 pp. [Available online at https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/290685/scho0505bjdz-e-e.pdf.]

  • Tennant, W., 2015: Improving initial condition perturbations for MOGREPS-UK. Quart. J. Roy. Meteor. Soc., 141, 2324–2336, doi:10.1002/qj.2524.

    • Search Google Scholar
    • Export Citation

  • Tennant, W., and Beare S. , 2014: New schemes to perturb sea-surface temperature and soil moisture content in MOGREPS. Quart. J. Roy. Meteor. Soc., 140, 1150–1160, doi:10.1002/qj.2202.

    • Search Google Scholar
    • Export Citation

  • Theis, S. E., Hense A. , and Damrath U. , 2005: Probabilistic precipitation forecasts from a deterministic model: A pragmatic approach. Meteor. Appl., 12, 257–268, doi:10.1017/S1350482705001763.

    • Search Google Scholar
    • Export Citation

  • Thrush, D., Burningham K. , and Fielding J. , 2005: Flood warning for vulnerable groups: A qualitative study. R&D Tech. Rep. W5C-018/3, Environment Agency, 73 pp. [Available online at http://www.envirobase.info/PDF/3557_1.pdf.]

  • Tracton, M. S., and Kalnay E. , 1993: Operational ensemble prediction at the National Meteorological Center: Practical aspects. Wea. Forecasting, 8, 379–398, doi:10.1175/1520-0434(1993)008<0379:OEPATN>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Tracton, M. S., Du J. , Toth Z. , and Juang H. , 1998: Short-Range Ensemble Forecasting (SREF) at NCEP/EMC. Proc. 12th Conf. on Numerical Weather Prediction, Phoenix, AZ, Amer. Meteor. Soc., 269–272.

  • Twigger-Ross, C., Fernandez-Bilbao A. , Tapsell S. , Walker G. , Watson N. , Deeming H. , and Kashefi E. , 2008: Improving flood warnings: Final report. Improving institutional and social responses to flooding, Science Rep. SC060019, Work Package 1a, Environment Agency, 76 pp.

  • Vié, B., Nuissier O. , and Ducrocq V. , 2011: Cloud-resolving ensemble simulations of Mediterranean heavy precipitating events: Uncertainty on initial conditions and lateral boundary conditions. Mon. Wea. Rev., 139, 403–423, doi:10.1175/2010MWR3487.1.

    • Search Google Scholar
    • Export Citation

  • Vié, B., Molinié G. , Nuissier O. , Vincendon B. , Ducrocq V. , Bouttier F. , and Richard E. , 2012: Hydrometeorological evaluation of a convection-permitting ensemble prediction system for Mediterranean heavy precipitating events. Nat. Hazards Earth Syst. Sci., 12, 2631–2645, doi:10.5194/nhess-12-2631-2012.

    • Search Google Scholar
    • Export Citation

  • Walser, A., Luthi D. , and Schar C. , 2004: Predictability of precipitation in a cloud-resolving model. Mon. Wea. Rev., 132, 560–577, doi:10.1175/1520-0493(2004)132<0560:POPIAC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Waters, E., Weinstein N. , Colditz G. , and Emmons K. , 2006: Formats for improving risk communication in medical trade off decisions. J. Health Commun., 11, 167–182, doi:10.1080/10810730500526695.

    • Search Google Scholar
    • Export Citation

  • Wedawatta, G., Ingirige B. , and Proverbs D. , 2014: Small businesses and flood impacts: The case of the 2009 flood event in Cockermouth. J. Flood Risk Manage., 7, 42–53, doi:10.1111/jfr3.12031.

    • Search Google Scholar
    • Export Citation

  • Weusthoff, T., Ament F. , and Arpagaus M. , 2010: Assessing the benefits of convection-permitting models by neighborhood verification: Examples from MAP D-PHASE. Mon. Wea. Rev., 138, 3418–3433, doi:10.1175/2010MWR3380.1.

    • Search Google Scholar
    • Export Citation

  • Wikipedia, 2015: Hootsuite. Accessed 28 March 2016. [Available online at https://en.wikipedia.org/wiki/Hootsuite.]

  • Wilson, D., and Ballard S. P. , 1999: A microphysically based precipitation scheme for the UK Meteorological Office Unified Model. Quart. J. Roy. Meteor. Soc., 125, 1607–1636, doi:10.1002/qj.49712555707.

    • Search Google Scholar
    • Export Citation

  • Yamagishi, I., 1997: When a 12.86% mortality is more dangerous than 24.14%: Implications for risk communication. Appl. Cognit. Psychol., 11, 495–506, doi:10.1002/(SICI)1099-0720(199712)11:6<495::AID-ACP481>3.0.CO;2-J.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1290 515 19
PDF Downloads 309 101 2