Regionalizing Rainfall at Very High Resolution over La Réunion Island Using a Regional Climate Model

Béatrice Morel LE2P, Université de la Réunion, St-Denis, France

Search for other papers by Béatrice Morel in
Current site
Google Scholar
PubMed
Close
,
Benjamin Pohl CRC/Biogéosciences, UMR6282, CNRS/Université de Bourgogne, Dijon, France

Search for other papers by Benjamin Pohl in
Current site
Google Scholar
PubMed
Close
,
Yves Richard CRC/Biogéosciences, UMR6282, CNRS/Université de Bourgogne, Dijon, France

Search for other papers by Yves Richard in
Current site
Google Scholar
PubMed
Close
,
Benjamin Bois CRC/Biogéosciences, UMR6282, CNRS/Université de Bourgogne, Dijon, France

Search for other papers by Benjamin Bois in
Current site
Google Scholar
PubMed
Close
, and
Miloud Bessafi LE2P, Université de la Réunion, St-Denis, France

Search for other papers by Miloud Bessafi in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Regional climate models (RCMs) should be evaluated with respect to their ability to downscale large-scale climate information to the local scales, which are sometimes strongly modulated by surface conditions. This is the case for La Réunion (southwest Indian Ocean) because of its island context and its complex topography. Large-scale atmospheric configurations such as tropical cyclones (TCs) may have an amplifying effect on local rainfall patterns that only a very high-resolution RCM, forced by the large scales and resolving finescale processes, may simulate properly.

This paper documents the capability of the Weather Research and Forecasting Model (WRF) RCM to regionalize rainfall variability at very high resolution (680 m) over La Réunion island for daily to seasonal time scales and year-to-year differences. Two contrasted wet seasons (November–April) are selected: 2000–01 (abnormally dry) and 2004–05 (abnormally wet). WRF rainfall is compared to a dense network of rain gauge records interpolated onto the WRF grid through the regression-kriging (RK) technique. RK avoids the point-to-grid comparison issue, but produces imperfect estimates due to sampling, so its quality also needs to be tested.

Seasonal rainfall amounts and contrasts produced by WRF are fairly realistic. At intraseasonal and daily time scales, differences to RK are more sizable. These differences are not easy to interpret in sectors where the rain gauge network is less dense and the quality of RK more uncertain, as over the eastern slopes of Piton de la Fournaise volcano where WRF seems to simulate more realistic rainfall than RK. Finally, the heavy rainfall associated with TC Ando on 6 January 2001, is documented. WRF shows weak disagreements with RK, indicating its capability to regionalize rainfall during extreme events.

Corresponding author address: Dr. Béatrice Morel, Laboratoire d’Energétique, d’Electronique et Procédés, 15, Avenue René Cassin, CS 92003, 97744 Saint-Denis CEDEX 9, France. E-mail: beatrice.morel@univ-reunion.fr

Abstract

Regional climate models (RCMs) should be evaluated with respect to their ability to downscale large-scale climate information to the local scales, which are sometimes strongly modulated by surface conditions. This is the case for La Réunion (southwest Indian Ocean) because of its island context and its complex topography. Large-scale atmospheric configurations such as tropical cyclones (TCs) may have an amplifying effect on local rainfall patterns that only a very high-resolution RCM, forced by the large scales and resolving finescale processes, may simulate properly.

This paper documents the capability of the Weather Research and Forecasting Model (WRF) RCM to regionalize rainfall variability at very high resolution (680 m) over La Réunion island for daily to seasonal time scales and year-to-year differences. Two contrasted wet seasons (November–April) are selected: 2000–01 (abnormally dry) and 2004–05 (abnormally wet). WRF rainfall is compared to a dense network of rain gauge records interpolated onto the WRF grid through the regression-kriging (RK) technique. RK avoids the point-to-grid comparison issue, but produces imperfect estimates due to sampling, so its quality also needs to be tested.

Seasonal rainfall amounts and contrasts produced by WRF are fairly realistic. At intraseasonal and daily time scales, differences to RK are more sizable. These differences are not easy to interpret in sectors where the rain gauge network is less dense and the quality of RK more uncertain, as over the eastern slopes of Piton de la Fournaise volcano where WRF seems to simulate more realistic rainfall than RK. Finally, the heavy rainfall associated with TC Ando on 6 January 2001, is documented. WRF shows weak disagreements with RK, indicating its capability to regionalize rainfall during extreme events.

Corresponding author address: Dr. Béatrice Morel, Laboratoire d’Energétique, d’Electronique et Procédés, 15, Avenue René Cassin, CS 92003, 97744 Saint-Denis CEDEX 9, France. E-mail: beatrice.morel@univ-reunion.fr
Save
  • Baldy, S., G. Ancellet, M. Bessafi, A. Badr, and J. D. Lan San Luk, 1996: Field observations of the vertical distribution of tropospheric ozone at the island of Reunion (southern tropics). J. Geophys. Res., 101, 23 83523 849, doi:10.1029/95JD02929.

    • Search Google Scholar
    • Export Citation
  • Barcelo, A., and J. Coudray, 1996: Nouvelle carte des isohyètes annuelles et des maxima pluviométriques sur le massif du Piton de le Fournaise (île de La Réunion). Rev. Sci. Eau,9, 457–484, doi:10.7202/705262ar.

  • Barcelo, A., R. Robert, and J. Coudray, 1997: A major rainfall event: The 27 February–5 March 1993 rains on the southeastern slope of Piton de la Fournaise Massif (Reunion Island, Southwest Indian Ocean). Mon. Wea. Rev., 125, 33413346, doi:10.1175/1520-0493(1997)125<3341:AMRETF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Blamey, R. C., and C. J. C. Reason, 2009: Numerical simulation of a mesoscale convective system over the east coast of South Africa. Tellus, 61A, 1734, doi:10.1111/j.1600-0870.2008.00366.x.

    • Search Google Scholar
    • Export Citation
  • Boulard, D., B. Pohl, J. Crétat, N. Vigaud, and T. Pham-Xuan, 2013: Downscaling large-scale climate variability using a regional climate model: The case of ENSO over Southern Africa. Climate Dyn., 40, 11411168, doi:10.1007/s00382-012-1400-6.

    • Search Google Scholar
    • Export Citation
  • Casola, J. H., and J. M. Wallace, 2007: Identifying weather regimes in the wintertime 500-hPa geopotential height field for the Pacific–North American sector using a limited-contour clustering technique. J. Appl. Meteor. Climatol., 46, 16191630, doi:10.1175/JAM2564.1.

    • Search Google Scholar
    • Export Citation
  • Chen, F., and J. Dudhia, 2001a: Coupling an advanced land-surface/hydrology model with the Penn State/NCAR MM5 modeling system. Part I: Model description and implementation. Mon. Wea. Rev., 129, 569585, doi:10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Chen, F., and J. Dudhia, 2001b: Coupling an advanced land-surface/hydrology model with the Penn State/NCAR MM5 modeling system. Part II: Model validation. Mon. Wea. Rev., 129, 587604, doi:10.1175/1520-0493(2001)129<0587:CAALSH>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Cheng, X., and J. M. Wallace, 1993: Cluster analysis of the Northern Hemisphere wintertime 500-hPa height field: Spatial patterns. J. Atmos. Sci., 50, 26742696, doi:10.1175/1520-0469(1993)050<2674:CAOTNH>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Cressie, N. A. C., 1993: Statistics for Spatial Data. Wiley-Interscience, 928 pp.

  • Crétat, J., and B. Pohl, 2012: How physical parameterizations can modulate internal variability in a regional climate model. J. Atmos. Sci., 69, 714724, doi:10.1175/JAS-D-11-0109.1.

    • Search Google Scholar
    • Export Citation
  • Crétat, J., C. Macron, B. Pohl, and Y. Richard, 2011: 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, 2012a: 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
  • Crétat, J., Y. Richard, B. Pohl, M. Rouault, C. J. C. Reason, and N. Fauchereau, 2012b: Recurrent daily rainfall patterns over South Africa and associated dynamics during the core of the austral summer. Int. J. Climatol., 32, 261273, doi:10.1002/joc.2266.

    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and Coauthors, 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
  • Diaconescu, E. P., and R. Laprise, 2013: Can added value be expected in RCM-simulated large scales? Climate Dyn., 41, 1769–1800, doi:10.1007/s00382-012-1649-9.

    • Search Google Scholar
    • Export Citation
  • Dudhia, J., 1989: Numerical study of convection observed during the winter 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
  • Goovaerts, P., 2000: Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. J. Hydrol., 228, 113129, doi:10.1016/S0022-1694(00)00144-X.

    • Search Google Scholar
    • Export Citation
  • Hengl, T., 2009: A Practical Guide to Geostatistical Mapping. University of Amsterdam, 291 pp.

  • Hengl, T., G. B. M. Heuvelink, and D. G. Rossiter, 2007: About regression-kriging: From equations to case studies. Comput. Geosci., 33, 13011315, doi:10.1016/j.cageo.2007.05.001.

    • Search Google Scholar
    • Export Citation
  • Hocking, R. R., 1976: The analysis and selection of variables in linear regression. Biometrics, 32, 140, doi:10.2307/2529336.

  • Hong, S. Y., and J.-O. J. Lim, 2006: The WRF Single-Moment 6-Class microphysics scheme (WSM6). J. Korean Meteor. Soc., 42, 129151.

  • 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
  • Hutchinson, T. A., 2007: An adaptive timestep for increased model efficiency. Extended Abstracts, Eighth WRF Users’ Workshop, Boulder, CO, UCAR, 4 pp. [Available online at http://www2.mmm.ucar.edu/wrf/users/workshops/WS2007/abstracts/9-4_Hutchinson.pdf.]

  • Isaaks, E., and R. Srivastava, 1989: An Introduction to Applied Geostatistics. Oxford University Press, 561 pp.

  • Joly, D., T. Brossard, H. Cardot, J. Cavailhes, M. Hilal, and P. Wavresky, 2011: Temperature interpolation based on local information: The example of France. Int. J. Climatol., 31, 21412153, doi:10.1002/joc.2220.

    • Search Google Scholar
    • Export Citation
  • Kain, J. S., 2004: The Kain–Fritsch convective parameterization: An update. J. Appl. Meteor., 43, 170181, doi:10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Kyriakidis, P. C., J. Kim, and N. L. Miller, 2001: Geostatistical mapping of precipitation from rain gauge data using atmospheric terrain characteristics. J. Appl. Meteor., 40, 18551877, doi:10.1175/1520-0450(2001)040<1855:GMOPFR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Lloyd, C. D., 2010: Nonstationary models for exploring and mapping monthly precipitation in the United Kingdom. Int. J. Climatol., 30, 390405, doi:10.1002/joc.1892.

    • Search Google Scholar
    • Export Citation
  • Ma, L.-M., and Z.-M. Tan, 2009: Improving the behavior of the cumulus parameterization for tropical cyclone prediction: Convection trigger. Atmos. Res., 92, 190211, doi:10.1016/j.atmosres.2008.09.022.

    • Search Google Scholar
    • Export Citation
  • Martineu, C., J. Y. Caneill, and R. Sadourny, 1999: Potential predictability of European winters from the analysis of seasonal simulations with an AGCM. J. Climate, 12, 30333061, doi:10.1175/1520-0442(1999)012<3033:PPOEWF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Matheron, G., 1969: Le krigeage universel. Vol. 1. Cahiers du Centre de Morphologie Mathématique, Ecole des Mines de Paris, Fontainebleau, Paris, France.

  • Matheron, G., 1971: The theory of regionalized variables and its applications. Tech. Rep. 6, Paris School of Mines, Cahiers du Centre de Morphologie Mathématique., Fontainebleau, Paris, France, 218 pp. [Available online at http://cg.ensmp.fr/bibliotheque/public/MATHERON_Ouvrage_00167.pdf.]

  • Mayes, J., 2007: Weather news. Weather, 62, 114, doi:10.1002/wea.94.

  • Mlawer, E., S. Taubman, P. Brown, M. Iacono, and S. Clough, 1997: Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the long-wave. J. Geophys. Res., 102, 16 66316 682, doi:10.1029/97JD00237.

    • Search Google Scholar
    • Export Citation
  • Moron, V., A. W. Robertson, N. M. Ward, and P. Camberlin, 2007: Spatial coherence of tropical rainfall at the regional scale. J. Climate, 20, 52445263, doi:10.1175/2007JCLI1623.1.

    • Search Google Scholar
    • Export Citation
  • Odeh, I. O. A., A. B. McBratney, and D. J. Chittleborough, 1995: Further results on prediction of soil properties from terrain attributes: Heterotopic cokriging and regression-kriging. Geoderma, 67, 215226, doi:10.1016/0016-7061(95)00007-B.

    • Search Google Scholar
    • Export Citation
  • Oehler, J. F., J. F. Lénat, and P. Labazuy, 2008: Growth and collapse of the Reunion Island volcanoes. Bull. Volcanol., 70, 717742, doi:10.1007/s00445-007-0163-0.

    • Search Google Scholar
    • Export Citation
  • Oettli, P., and P. Camberlin, 2005: Influence of topography on monthly rainfall distribution over East Africa. Climate Res., 28, 199212, doi:10.3354/cr028199.

    • Search Google Scholar
    • Export Citation
  • Pohl, B., and P. Camberlin, 2014: A typology for intraseasonal oscillations. Int. J. Climatol.,34, 430–445, doi:10.1002/joc.3696.

  • Pohl, B., and J. Crétat, 2014: On the use of nudging techniques for regional climate modeling: Application for tropical convection. Climate Dyn., doi:10.1007/s00382-013-1994-3, in press.

    • Search Google Scholar
    • Export Citation
  • Pohl, B., M. Rouault, and S. S. Roy, 2014: Simulation of the annual and diurnal cycles of rainfall over South Africa by a regional climate model. Climate Dyn., doi:10.1007/s00382-013-2046-8, in press.

    • Search Google Scholar
    • Export Citation
  • Prudhomme, C., and D. W. Reed, 1999: Mapping extreme rainfall in a mountainous region using geostatistical techniques: A case study in Scotland. Int. J. Climatol., 19, 13371356, doi:10.1002/(SICI)1097-0088(199910)19:12<1337::AID-JOC421>3.0.CO;2-G.

    • Search Google Scholar
    • Export Citation
  • Ratna, S. B., J. V. Ratnam, S. K. Behera, C. J. deW. Rautenbach, T. Ndarna, 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., and Coauthors, 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
  • Schuurmans, J. M., M. F. P. Bierkens, E. J. Pebesma, and R. Uijlenhoet, 2007: Automatic prediction of high-resolution daily rainfall fields for multiple extents: The potential of operational radar. J. Hydrometeor., 8, 12041224, doi:10.1175/2007JHM792.1.

    • Search Google Scholar
    • Export Citation
  • Simmons, A., S. Uppala, D. Dee, and S. Kobayashi, 2007: ERA-Interim: New ECMWF reanalysis products from 1989 onwards. ECMWF Newsletter, No. 110, ECMWF, Reading, United Kingdom, 2535.

  • Skamarock, W. C., and Coauthors, 2008: A description of the Advanced Research WRF version 3. NCAR Tech. Note NCAR/TN-475+STR, 113 pp. [Available online at http://www.mmm.ucar.edu/wrf/users/docs/arw_v3_bw.pdf.]

  • Stow, C. D., and K. N. Dirks, 1998: High-resolution studies of rainfall on Norfolk Island. Part 1: The spatial variability of rainfall. J. Hydrol., 208, 163186, doi:10.1016/S0022-1694(98)00154-1.

    • Search Google Scholar
    • Export Citation
  • Taupin, F. G., M. Bessafi, S. Baldy, and P. J. Bremaud, 1999: Tropospheric ozone above the southwestern Indian Ocean is strongly linked to dynamical conditions prevailing in the tropics. J. Geophys. Res., 104, 80578066, doi:10.1029/98JD02456.

    • Search Google Scholar
    • Export Citation
  • van den Heever, S. C., P. C. D’Abreton, and P. D. Tyson, 1997: Numerical simulation of tropical-temperate troughs over southern Africa using the CSU RAMS model. S. Afr. J. Sci., 93, 359365.

    • Search Google Scholar
    • Export Citation
  • Vigaud, N., B. Pohl, and J. Crétat, 2012: Tropical–temperate interactions over southern Africa simulated by a regional climate model. Climate Dyn., 39, 28952916, doi:10.1007/s00382-012-1314-3.

    • Search Google Scholar
    • Export Citation
  • Wang, Y., L. R. Leung, J. L. McGregor, D.-K. Lee, W.-C. Wang, Y. Ding, and F. Kimura, 2004: Regional climate modeling: Progress, challenges, and prospects. J. Meteor. Soc. Japan, 82, 15991628, doi:10.2151/jmsj.82.1599.

    • Search Google Scholar
    • Export Citation
  • Ward, J. H., 1963: Hierarchical grouping to optimize an objective function. J. Amer. Stat. Assoc., 58, 236244, doi:10.1080/01621459.1963.10500845.

    • Search Google Scholar
    • Export Citation
  • Williams, C. J. R., D. R. Kniveton, and R. Layberry, 2010: Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa. Theor. Appl. Climatol., 99, 927, doi:10.1007/s00704-009-0124-y.

    • Search Google Scholar
    • Export Citation
  • Yu, N., C. Barthe, and M. Plu, 2014: Evaluating intense precipitation in high-resolution numerical model over a tropical island: Impact of model horizontal resolution. Nat. Hazards Earth Syst. Sci. Discuss., 2, 9991031, doi:10.5194/nhessd-2-999-2014.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 311 100 1
PDF Downloads 214 85 5