• Beraki, A. F., , D. G. DeWitt, , W. A. Landman, , and C. Olivier, 2014: Dynamical seasonal climate prediction using an ocean–atmosphere coupled climate model developed in partnership between South Africa and the IRI. J. Climate, 27, 17191741, doi:10.1175/JCLI-D-13-00275.1.

    • Search Google Scholar
    • Export Citation
  • Betts, A. K., , and M. J. Miller, 1986: A new convective adjustment scheme. Part II: Single column tests using GATE wave, BOMEX, and arctic air-mass data sets. Quart. J. Roy. Meteor. Soc., 112, 693709, doi:10.1002/qj.49711247308.

    • Search Google Scholar
    • Export Citation
  • Bruyère, C. L., , J. M. Done, , G. J. Holland, , and S. Fredrick, 2014: Bias corrections of global models for regional climate simulations of high-impact weather. Climate Dyn., 43, 18471856, doi:10.1007/s00382-013-2011-6.

    • Search Google Scholar
    • Export Citation
  • Christensen, O. B., , J. H. Christensen, , B. Machenhauer, , and M. Botzet, 1998: Very high-resolution regional climate simulations over Scandinavia—Present climate. J. Climate, 11, 32043229, doi:10.1175/1520-0442(1998)011<3204:VHRRCS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Crétat, J., , C. Macron, , B. Pohl, , and Y. Richard, 2011a: Quantifying internal variability in a regional climate model: A case study for southern Africa. Climate Dyn., 37, 13351356, doi:10.1007/s00382-011-1021-5.

    • Search Google Scholar
    • Export Citation
  • Crétat, J., , B. Pohl, , Y. Richard, , and P. Drobinski, 2011b: Uncertainties in simulating regional climate of southern Africa: Sensitivity to physical parameterizations using WRF. Climate Dyn., 38, 613634, doi:10.1007/s00382-011-1055-8.

    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and et al. , 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597, doi:10.1002/qj.828.

    • Search Google Scholar
    • Export Citation
  • Dickinson, R. E., , R. M. Errico, , F. Giorgi, , and G. T. Bates, 1989: A regional climate model for the western United States. Climatic Change, 15, 383422, doi:10.1007/BF00240465.

    • Search Google Scholar
    • Export Citation
  • Doi, T., and et al. , 2014: Annual report of the Earth Simulator: April 2014–March 2015. Center for Earth Information Science and Technology Rep., 147 pp. [Available online at http://www.jamstec.go.jp/ceist/j/publication/annual/annual2014/pdf/AnnualReport_ES_2015.pdf.]

  • Dudhia, J., 1989: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46, 30773107, doi:10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Giorgi, F., , and G. T. Bates, 1989: The climatological skill of a regional model over complex terrain. Mon. Wea. Rev., 117, 23252347, doi:10.1175/1520-0493(1989)117<2325:TCSOAR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Hansingo, K., , and C. J. C. Reason, 2008: Modeling the atmospheric response to SST dipole patterns in the south Indian Ocean with a regional climate model. Meteor. Atmos. Phys., 100, 3752, doi:10.1007/s00703-008-0294-7.

    • Search Google Scholar
    • Export Citation
  • Holland, G. J., , J. M. Done, , C. L. Bruyère, , C. Cooper, , and A. Suzuki, 2010: Model investigations of the effects of climate variability and change on future Gulf of Mexico tropical cyclone activity. Offshore Technology Conf., Houston, TX, Offshore Technology Conference, OTC-20690-MS, doi:10.4043/20690-MS.

  • Hong, S. Y., , J. Dudhia, , and S. H. Chen, 2004: A revised approach to ice microphysical processes for bulk parameterization of cloud and precipitation. Mon. Wea. Rev., 132, 103120, doi:10.1175/1520-0493(2004)132<0103:ARATIM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Hong, S. Y., , Y. Noh, , and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 23182341, doi:10.1175/MWR3199.1.

    • Search Google Scholar
    • Export Citation
  • Huffman, G. J., , R. F. Adler, , M. Morrissey, , D. T. Bolvin, , S. Curtis, , R. Joyce, , B. McGavock, , and J. Susskind, 2001: Global precipitation at one-degree daily resolution from multisatellite observations. J. Hydrometeor., 2, 3650, doi:10.1175/1525-7541(2001)002<0036:GPAODD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Huffman, G. J., and et al. , 2007: The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-global multiyear, combined-sensor precipitation estimates at fine scale. J. Hydrometeor., 8, 3855, doi:10.1175/JHM560.1.

    • Search Google Scholar
    • Export Citation
  • Janjić, Z. I., 1994: The step-mountain eta coordinate model: Further developments of the convection, viscous sublayer, and turbulence closure schemes. Mon. Wea. Rev., 122, 927945, doi:10.1175/1520-0493(1994)122<0927:TSMECM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Joubert, A. M., , and B. C. Hewitson, 1997: Simulating present and future climate changes of southern Africa using general circulation models. Prog. Phys. Geogr., 21, 5178, doi:10.1177/030913339702100104.

    • Search Google Scholar
    • Export Citation
  • Joubert, A. M., , J. J. Katzfey, , J. L. McGregor, , and K. C. Nguyan, 1999: Simulating midsummer climate over southern Africa using a nested regional climate model. J. Geophys. Res., 104, 19 01519 025, doi:10.1029/1999JD900256.

    • Search Google Scholar
    • Export Citation
  • Kgatuke, M. M., , W. A. Landman, , A. Beraki, , and M. P. Mbedzi, 2008: The internal variability of the RegCM3 over South Africa. Int. J. Climatol., 28, 505520, doi:10.1002/joc.1550.

    • Search Google Scholar
    • Export Citation
  • Landman, W. A., 2014: How the International Research Institute for Climate and Society has contributed towards seasonal climate forecast modelling and operations in South Africa. Earth Perspect., 1, doi:10.1186/2194-6434-1-22.

    • Search Google Scholar
    • Export Citation
  • Landman, W. A., , and S. J. Mason, 1999: Operational long-lead prediction of South African rainfall using canonical correlation analysis. Int. J. Climatol., 19, 10731090, doi:10.1002/(SICI)1097-0088(199908)19:10<1073::AID-JOC415>3.0.CO;2-J.

    • Search Google Scholar
    • Export Citation
  • Landman, W. A., , M. M. Kgatuke, , M. Mbedzi, , A. Beraki, , A. Bartman, , and A. du Piesanie, 2009: Performance comparison of some dynamical and empirical downscaling methods for South Africa from a seasonal climate modelling perspective. Int. J. Climatol., 29, 15351549, doi:10.1002/joc.1766.

    • Search Google Scholar
    • Export Citation
  • Landman, W. A., , D. DeWitt, , D.-E. Lee, , A. Beraki, , and D. Lötter, 2012: Seasonal rainfall prediction skill over South Africa: One- versus two-tiered forecasting systems. Wea. Forecasting, 27, 489501, doi:10.1175/WAF-D-11-00078.1.

    • Search Google Scholar
    • Export Citation
  • Landman, W. A., , A. Beraki, , D. DeWitt, , and D. Lötter, 2014: SST prediction methodologies and verification considerations for dynamical mid-summer rainfall forecasts for South Africa. Water SA, 40, 615622, doi:10.4314/wsa.v40i4.6.

    • Search Google Scholar
    • Export Citation
  • Luo, J.-J., , S. Masson, , E. Roeckner, , G. Madec, , and T. Yamagata, 2005: Reducing climatology bias in an ocean–atmosphere CGCM with improved coupling physics. J. Climate, 18, 23442360, doi:10.1175/JCLI3404.1.

    • Search Google Scholar
    • Export Citation
  • MacKellar, N. C., , M. A. Tadros, , and B. C. Hewitson, 2009: Effects of vegetation map change in MM5 simulations of southern Africa’s summer climate. Int. J. Climatol., 29, 885898, doi:10.1002/joc.1754.

    • Search Google Scholar
    • Export Citation
  • Madec, G., 2006: NEMO ocean engine. Note du Pôle de Modélisation IPSL Rep., 110 pp.

  • Mason, S. J., , and N. E. Graham, 1999: Conditional probabilities, relative operating characteristics, and relative operating levels. Wea. Forecasting, 14, 713725, doi:10.1175/1520-0434(1999)014<0713:CPROCA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Mason, S. J., , and N. E. Graham, 2002: Areas beneath the relative operating characteristics (ROC) and relative operating levels (ROL) curves: Statistical significance and interpretation. Quart. J. Roy. Meteor. Soc., 128, 21452166, doi:10.1256/003590002320603584.

    • Search Google Scholar
    • Export Citation
  • Misra, V., , and M. Kanamitsu, 2004: Anomaly nesting: A methodology to downscale seasonal climate simulations from AGCMs. J. Climate, 17, 32493262, doi:10.1175/1520-0442(2004)017<3249:ANAMTD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Mlawer, E. J., , S. J. Taubman, , P. D. Brown, , M. J. Iacono, , and S. A. Clough, 1997: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102, 16 66316 682, doi:10.1029/97JD00237.

    • Search Google Scholar
    • Export Citation
  • Novella, N. S., , and W. M. Thiaw, 2013: African Rainfall Climatology version 2 for famine early warning systems. J. Appl. Meteor. Climatol., 52, 588606, doi:10.1175/JAMC-D-11-0238.1.

    • Search Google Scholar
    • Export Citation
  • Ratna, S. B., , J. V. Ratnam, , S. K. Behera, , C. J. de W. Rautenbach, , T. Ndarana, , K. Takahashi, , and T. Yamagata, 2014: Performance assessment of three convective parameterization schemes in WRF for downscaling summer rainfall over South Africa. Climate Dyn., 42, 29312953, doi:10.1007/s00382-013-1918-2.

    • Search Google Scholar
    • Export Citation
  • Ratnam, J. V., , S. K. Behera, , Y. Masumoto, , K. Takahashi, , and T. Yamagata, 2012: A simple regional coupled model experiment for summer-time climate simulation over southern Africa. Climate Dyn., 39, 22072217, doi:10.1007/s00382-011-1190-2.

    • Search Google Scholar
    • Export Citation
  • Ratnam, J. V., and et al. , 2013: Dynamical downscaling of austral summer climate forecasts over southern Africa using a regional coupled model. J. Climate, 26, 60156032, doi:10.1175/JCLI-D-12-00645.1.

    • Search Google Scholar
    • Export Citation
  • Ratnam, J. V., , S. K. Behera, , Y. Masumoto, , and T. Yamagata, 2014: Remote effects of El Niño and Modoki events on the austral summer precipitation of southern Africa. J. Climate, 27, 38023815, doi:10.1175/JCLI-D-13-00431.1.

    • Search Google Scholar
    • Export Citation
  • Ratnam, J. V., , Y. Morioka, , S. K. Behera, , and T. Yamagata, 2015: A model study of regional air–sea interaction in the austral summer precipitation over southern Africa. J. Geophys. Res. Atmos., 120, 23422357, doi:10.1002/2014JD022154.

    • Search Google Scholar
    • Export Citation
  • Reynolds, R. W., , N. A. Rayner, , T. M. Smith, , D. C. Stokes, , and W. Wang, 2002: An improved in situ and satellite SST analysis for climate. J. Climate, 15, 16091625, doi:10.1175/1520-0442(2002)015<1609:AIISAS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Roeckner, E., and et al. , 2003: The atmospheric general circulation model ECHAM5. Part I: Model description. Max-Planck-Institut für Meteorologie Rep. 349, 127 pp. [Available online at https://www.mpimet.mpg.de/fileadmin/publikationen/Reports/max_scirep_349.pdf.]

  • Sasaki, W., , K. J. Richards, , and J. J. Luo, 2012: Role of vertical mixing originating from small vertical scale structures above and within the equatorial thermocline in an OGCM. Ocean Modell., 57–58, 2942, doi:10.1016/j.ocemod.2012.09.002.

    • Search Google Scholar
    • Export Citation
  • Sasaki, W., , K. J. Richards, , and J. J. Luo, 2013: Impact of vertical mixing induced by small vertical scale structures above and within the equatorial thermocline on the tropical Pacific in a CGCM. Climate Dyn., 41, 443453, doi:10.1007/s00382-012-1593-8.

    • Search Google Scholar
    • Export Citation
  • Sasaki, W., , T. Doi, , K. J. Richards, , and Y. Masumoto, 2014: Impact of the equatorial Atlantic sea surface temperature on the tropical Pacific in a CGCM. Climate Dyn., 43, 25392552, doi:10.1007/s00382-014-2072-1.

    • Search Google Scholar
    • Export Citation
  • Sasaki, W., , T. Doi, , K. J. Richards, , and Y. Masumoto, 2015: The influence of ENSO on the equatorial Atlantic precipitation through the Walker circulation in a CGCM. Climate Dyn., 44, 191202, doi:10.1007/s00382-014-2133-5.

    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., , J. B. Klemp, , J. Dudhia, , D. O. Gill, , D. M. Barker, , W. Wang, , and J. G. Powers, 2005: A description of the Advanced Research WRF version 2. NCAR Tech. Note NCAR/TN-468+STR, 88 pp. [Available online at http://www2.mmm.ucar.edu/wrf/users/docs/arw_v2.pdf.]

  • Tadross, M. A., , W. J. Gutowski, , B. C. Hewitson, , C. Jack, , and M. New, 2006: MM5 simulations of interannual change and the diurnal cycle of southern African regional climate. Theor. Appl. Climatol., 86, 6380, doi:10.1007/s00704-005-0208-2.

    • Search Google Scholar
    • Export Citation
  • Valcke, S., , A. Caubel, , R. Vogelsang, , and D. Declat, 2004: OASIS3 ocean atmosphere sea ice soil user’s guide. CERFACS Tech. Rep. TR/CMGC/04/68, 73 pp .

  • White, R. H., , and R. Toumi, 2013: The limitations of bias correcting regional climate model inputs. Geophys. Res. Lett., 40, 29072912, doi:10.1002/grl.50612.

    • Search Google Scholar
    • Export Citation
  • Wilks, D., 1995: Statistical Methods in the Atmospheric Sciences: An Introduction. International Geophysics Series, Vol. 59, Elsevier, 467 pp.

  • Xu, Z., , and Z.-L. Yang, 2012: An improved dynamical downscaling method with GCM bias corrections and its validation with 30 years of climate simulations. J. Climate, 25, 62716286, doi:10.1175/JCLI-D-12-00005.1.

    • Search Google Scholar
    • Export Citation
  • Yuan, C., , T. Tozuka, , W. A. Landman, , and T. Yamagata, 2014: Dynamical seasonal prediction of southern African summer precipitation. Climate Dyn., 42, 33573374, doi:10.1007/s00382-013-1923-5.

    • Search Google Scholar
    • Export Citation
  • Yuan, X., , and X.-Z. Liang, 2011: Improving cold season precipitation prediction by the nested CWRF-CFS system. Geophys. Res. Lett., 38, L02706, doi:10.1029/2010GL046104.

    • Search Google Scholar
    • Export Citation
  • Yuan, X., , X.-Z. Liang, , and E. F. Wood, 2012: WRF ensemble downscaling seasonal forecasts of China winter precipitation during 1982–2008. Climate Dyn., 39, 20412058, doi:10.1007/s00382-011-1241-8.

    • Search Google Scholar
    • Export Citation
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Improvements to the WRF Seasonal Hindcasts over South Africa by Bias Correcting the Driving SINTEX-F2v CGCM Fields

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  • 1 Application Laboratory, JAMSTEC, Yokohama, Japan
  • | 2 Council for Scientific and Industrial Research, and Department of Geography, Geoinformatics and Meteorology, University of Pretoria, Pretoria, South Africa
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Abstract

In an attempt to improve the forecast skill of the austral summer precipitation over South Africa, an ensemble of 1-month-lead seasonal hindcasts generated by the Scale Interaction Experiment–Frontier Research Center for Global Change (SINTEX-F2v) coupled global circulation model is downscaled using the Weather Research and Forecasting (WRF) Model. The WRF Model with two-way interacting domains at horizontal resolutions of 27 and 9 km is used in the study. Evaluation of the deterministic skill score using the anomaly correlation coefficients shows that SINTEX-F2v has significant skill in precipitation forecasts confined to western regions of South Africa. Dynamical downscaling of SINTEX-F2v forecasts using the WRF Model is found to further improve the skill scores over South Africa. However, larger improvements in the skill scores are achieved when the WRF Model is forced by a form of bias-corrected SINTEX-F2v forecasts. The systematic biases in the original fields of the SITNEX-F2v forecasts are removed by superimposing the SINTEX-F2v 6-hourly anomalies over the ERA-Interim 6-hourly climatological fields. The WRF Model forced by the bias-corrected SINTEX-F2v shows significant skill in the forecast anomalies of precipitation over most parts of South Africa. Interestingly, the WRF Model runs with the bias correction did not help to improve the SINTEX-F2v forecast of 2-m air temperatures. Perhaps this is because of the large biases in the precipitation forecast by the WRF Model driven by the bias-corrected SINTEX-F2v. These results are important for potentially improving seasonal forecasts over South Africa.

Corresponding author address: J. V. Ratnam, Application Laboratory, JAMSTEC, 3173-25 Showa-machi, Kanazawa-ku, Yokohama, Kanagawa 236-0001, Japan. E-mail: jvratnam@jamstec.go.jp

Abstract

In an attempt to improve the forecast skill of the austral summer precipitation over South Africa, an ensemble of 1-month-lead seasonal hindcasts generated by the Scale Interaction Experiment–Frontier Research Center for Global Change (SINTEX-F2v) coupled global circulation model is downscaled using the Weather Research and Forecasting (WRF) Model. The WRF Model with two-way interacting domains at horizontal resolutions of 27 and 9 km is used in the study. Evaluation of the deterministic skill score using the anomaly correlation coefficients shows that SINTEX-F2v has significant skill in precipitation forecasts confined to western regions of South Africa. Dynamical downscaling of SINTEX-F2v forecasts using the WRF Model is found to further improve the skill scores over South Africa. However, larger improvements in the skill scores are achieved when the WRF Model is forced by a form of bias-corrected SINTEX-F2v forecasts. The systematic biases in the original fields of the SITNEX-F2v forecasts are removed by superimposing the SINTEX-F2v 6-hourly anomalies over the ERA-Interim 6-hourly climatological fields. The WRF Model forced by the bias-corrected SINTEX-F2v shows significant skill in the forecast anomalies of precipitation over most parts of South Africa. Interestingly, the WRF Model runs with the bias correction did not help to improve the SINTEX-F2v forecast of 2-m air temperatures. Perhaps this is because of the large biases in the precipitation forecast by the WRF Model driven by the bias-corrected SINTEX-F2v. These results are important for potentially improving seasonal forecasts over South Africa.

Corresponding author address: J. V. Ratnam, Application Laboratory, JAMSTEC, 3173-25 Showa-machi, Kanazawa-ku, Yokohama, Kanagawa 236-0001, Japan. E-mail: jvratnam@jamstec.go.jp
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