Dynamically Downscaled Climate Simulations of the Indian Monsoon in the Instrumental Era: Physics Parameterization Impacts and Precipitation Extremes

Yiling Huo Department of Physics, University of Toronto, Toronto, Ontario, Canada

Search for other papers by Yiling Huo in
Current site
Google Scholar
PubMed
Close
and
W. Richard Peltier Department of Physics, University of Toronto, Toronto, Ontario, Canada

Search for other papers by W. Richard Peltier in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

The complex orography of South Asia, including both the Himalayas and the Tibetan Plateau, renders the regional climate complex. How this climate, especially the monsoon circulations, will respond to the global warming process is important given the large population of the region. In a first step toward a contribution to the understanding of the expected impacts, a series of dynamically downscaled instrumental-era climate simulations for the Indian subcontinent are described and will serve as a basis for comparison against global warming simulations. Global simulations based upon the Community Earth System Model (CESM) are employed to drive a dynamical downscaling pipeline in which the Weather Research and Forecasting (WRF) Model is employed as regional climate model, in a nested configuration with two domains at 30- and 10-km resolution, respectively. The entire ensemble was integrated for 15 years (1980–94), with the global model representing a complete integration from the onset of Northern Hemisphere industrialization. Compared to CESM, WRF significantly improves the representation of orographic precipitation. Precipitation extremes are also characterized using extreme value analysis. To investigate the sensitivity of the South Asian summer monsoon simulation to different parameterization schemes, a small physics ensemble is employed. The Noah multiphysics (Noah-MP) land surface scheme reduces the summer warm bias compared to the Noah land surface scheme. Compared with the Kain–Fritsch cumulus scheme, the Grell-3 scheme produces an increased moisture bias at the first western rain barrier, whereas the Tiedtke scheme produces less precipitation over the subcontinent than observed. Otherwise the improvement of fit to the observations derived from applying the downscaling methodology is highly significant.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JAMC-D-18-0226.s1.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Yiling Huo, yhuo@physics.utoronto.ca

Abstract

The complex orography of South Asia, including both the Himalayas and the Tibetan Plateau, renders the regional climate complex. How this climate, especially the monsoon circulations, will respond to the global warming process is important given the large population of the region. In a first step toward a contribution to the understanding of the expected impacts, a series of dynamically downscaled instrumental-era climate simulations for the Indian subcontinent are described and will serve as a basis for comparison against global warming simulations. Global simulations based upon the Community Earth System Model (CESM) are employed to drive a dynamical downscaling pipeline in which the Weather Research and Forecasting (WRF) Model is employed as regional climate model, in a nested configuration with two domains at 30- and 10-km resolution, respectively. The entire ensemble was integrated for 15 years (1980–94), with the global model representing a complete integration from the onset of Northern Hemisphere industrialization. Compared to CESM, WRF significantly improves the representation of orographic precipitation. Precipitation extremes are also characterized using extreme value analysis. To investigate the sensitivity of the South Asian summer monsoon simulation to different parameterization schemes, a small physics ensemble is employed. The Noah multiphysics (Noah-MP) land surface scheme reduces the summer warm bias compared to the Noah land surface scheme. Compared with the Kain–Fritsch cumulus scheme, the Grell-3 scheme produces an increased moisture bias at the first western rain barrier, whereas the Tiedtke scheme produces less precipitation over the subcontinent than observed. Otherwise the improvement of fit to the observations derived from applying the downscaling methodology is highly significant.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JAMC-D-18-0226.s1.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Yiling Huo, yhuo@physics.utoronto.ca

Supplementary Materials

    • Supplemental Materials (PDF 1.06 MB)
Save
  • Ali, S., D. Li, F. Congbin, and Y. Yang, 2015: Performance of convective parameterization schemes in Asia using RegCM: Simulations in three typical regions for the period 1998–2002. Adv. Atmos. Sci., 32, 715730, https://doi.org/10.1007/s00376-014-4158-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • An, Z., J. Kutzbach, W. Prell, and S. Porter, 2001: Evolution of Asian monsoons and phased uplift of the Himalaya–Tibetan plateau since Late Miocene times. Nature, 411, 6266, https://doi.org/10.1038/35075035.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bolin, B., 1950: On the influence of the earth’s orography on the westerlies. Tellus, 2, 184195, https://doi.org/10.3402/tellusa.v2i3.8547.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Charney, J. G., and A. Eliassen, 1949: A numerical method for predicting in the perturbation of the middle latitude westerlies. Tellus, 1, 3854, https://doi.org/10.3402/tellusa.v1i2.8500.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chou, C., J. D. Neelin, and H. Su, 2001: Ocean–atmosphere–land feedbacks in an idealized monsoon. Quart. J. Roy. Meteor. Soc., 127, 18691891, https://doi.org/10.1002/qj.49712757602.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Coles, S., 2001: An Introduction to Statistical Modeling of Extreme Values. Springer Series in Statistics, Vol. 208, Springer, 209 pp., https://doi.org/10.1007/978-1-4471-3675-0.

    • Crossref
    • Export Citation
  • Cook, E. R., K. J. Anchukaitis, B. M. Buckley, R. D. D’Arrigo, G. C. Jacoby, and W. E. Wright, 2010: Asian monsoon failure and megadrought during the last millennium. Science, 328, 486489, https://doi.org/10.1126/science.1185188.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Davies, H., and R. E. Turner, 1977: Updating prediction models by dynamical relaxation: An examination of the technique. Quart. J. Roy. Meteor. Soc., 103, 225245, https://doi.org/10.1002/qj.49710343602.

    • Crossref
    • 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, https://doi.org/10.1002/qj.828.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Deser, C., A. Phillips, V. Bourdette, and H. Teng, 2012: Uncertainty in climate change projections: The role of internal variability. Climate Dyn., 38, 527546, https://doi.org/10.1007/s00382-010-0977-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • d’Orgeville, M., W. R. Peltier, A. R. Erler, and J. Gula, 2014: Climate change impacts on Great Lakes Basin precipitation extremes. J. Geophys. Res. Atmos., 119, 10 79910 812, https://doi.org/10.1002/2014JD021855.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Eggert, B., P. Berg, J. Haerter, D. Jacob, and C. Moseley, 2015: Temporal and spatial scaling impacts on extreme precipitation. Atmos. Chem. Phys., 15, 59575971, https://doi.org/10.5194/acp-15-5957-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., 1995: On thermally direct circulations in moist atmospheres. J. Atmos. Sci., 52, 15291536, https://doi.org/10.1175/1520-0469(1995)052<1529:OTDCIM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Erler, A. R., and W. R. Peltier, 2016: Projected changes in precipitation extremes for western Canada based on high-resolution regional climate simulations. J. Climate, 29, 88418863, https://doi.org/10.1175/JCLI-D-15-0530.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Erler, A. R., W. R. Peltier, and M. d’Orgeville, 2015: Dynamically downscaled high-resolution hydroclimate projections for western Canada. J. Climate, 28, 423450, https://doi.org/10.1175/JCLI-D-14-00174.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fita, L., J. Fernández, and M. Garcia-Dez, 2010: CLWRF: WRF modifications for regional climate simulation under future scenarios. 11th WRF Users’ Workshop, Boulder, CO, NCAR, P.26, http://www2.mmm.ucar.edu/wrf/users/workshops/WS2010/abstracts/P-26.pdf.

  • Flato, G., and Coauthors, 2013: Evaluation of climate models. Climate Change 2013: The Physical Science Basis, T. F. Stocker et al., Eds., Cambridge University Press, 741–866.

  • Flohn, H., 1968: Contributions to a meteorology of the Tibetan Highlands. Colorado State University Tech. Rep. 130, 120 pp.

  • Gent, P. R., and Coauthors, 2011: The Community Climate System Model version 4. J. Climate, 24, 49734991, https://doi.org/10.1175/2011JCLI4083.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Goswami, B. N., V. Venugopal, D. Sengupta, M. S. Madhusoodanan, and P. K. Xavier, 2006: Increasing trend of extreme rain events over India in a warming environment. Science, 314, 14421445, https://doi.org/10.1126/science.1132027.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grell, G. A., and D. Dévényi, 2002: A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophys. Res. Lett., 29, 1693, https://doi.org/10.1029/2002GL015311.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gula, J., and W. R. Peltier, 2012: Dynamical downscaling over the Great Lakes Basin of North America using the WRF regional climate model: The impact of the Great Lakes system on regional greenhouse warming. J. Climate, 25, 77237742, https://doi.org/10.1175/JCLI-D-11-00388.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guo, D., and H. Wang, 2016: Comparison of a very-fine-resolution GCM with RCM dynamical downscaling in simulating climate in China. Adv. Atmos. Sci., 33, 559, https://doi.org/10.1007/s00376-015-5147-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Harris, I., P. D. Jones, T. J. Osborn, and D. H. Lister, 2014: Updated high-resolution grids of monthly climatic observations—The CRU TS3.10 dataset. Int. J. Climatol., 34, 623642, https://doi.org/10.1002/joc.3711.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hartigan, J. A., and M. A. Wong, 1979: Algorithm AS 136: A K-means clustering algorithm. J. Roy. Stat. Soc., 28C, 100108.

  • Hawkins, E., T. M. Osborne, C. K. Ho, and A. J. Challinor, 2013: Calibration and bias correction of climate projections for crop modelling: An idealized case study over Europe. Agric. For. Meteor., 170, 1931, https://doi.org/10.1016/j.agrformet.2012.04.007.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hong, S.-Y., and J.-O. J. Lim, 2006: The WRF single-moment 6-class microphysics scheme (WSM6). J. Korean Meteor. Soc., 42, 129151.

  • Hosking, J. R. M., and J. R. Wallis, 1997: Regional Frequency Analysis: An Approach Based on L-Moments. Cambridge University Press, 240 pp.

    • Crossref
    • Export Citation
  • Hostetler, S. W., J. R. Alder, and A. M. Allan, 2011: Dynamically downscaled climate simulations over North America: Methods, evaluation and supporting documentation for users. U.S. Geological Survey Open-File Rep. 2011-1238, 64 pp.

    • Crossref
    • Export Citation
  • Iacono, M. J., J. S. Delamere, E. J. Mlawer, M. W. Shephard, S. A. Clough, and W. D. Collins, 2008: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. J. Geophys. Res., 113, D13103, https://doi.org/10.1029/2008JD009944.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ji, Z., and S. Kang, 2013: Double-nested dynamical downscaling experiments over the Tibetan Plateau and their projection of climate change under two RCP scenarios. J. Atmos. Sci., 70, 12781290, https://doi.org/10.1175/JAS-D-12-0155.1.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kripalani, R. H., A. Kulkarni, S. S. Sabade, and M. L. Khandekar, 2003: Indian monsoon variability in a global warming scenario. Nat. Hazards, 29, 189206, https://doi.org/10.1023/A:1023695326825.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kummerow, C., J. Simpson, O. Thiele, W. Barnes, A. T. C. Chang, E. Stocker, R. F. Adler, and A. Hou, 2000: The status of the tropical rainfall measuring mission (TRMM) after two years in orbit. J. Appl. Meteor., 39, 19651982, https://doi.org/10.1175/1520-0450(2001)040<1965:TSOTTR>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Loo, Y. Y., L. Billa, and A. Singh, 2014: Effect of climate change on seasonal monsoon in Asia and its impact on the variability of monsoon rainfall in Southeast Asia. Geosci. Front., 6, 817823, https://doi.org/10.1016/j.gsf.2014.02.009.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Menne, M. J., I. Durre, R. S. Vose, B. E. Gleason, and T. G. Houston, 2012: An overview of the Global Historical Climatology Network-Daily database. J. Atmos. Oceanic Technol., 29, 897910, https://doi.org/10.1175/JTECH-D-11-00103.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Miguez-Macho, G., G. L. Stenchikov, and A. Robock, 2004: Spectral nudging to eliminate the effects of domain position and geometry in regional climate model simulations. J. Geophys. Res., 109, D13104, https://doi.org/10.1029/2003JD004495.

    • Search Google Scholar
    • Export Citation
  • Mukhopadhyay, P., S. Taraphdar, B. N. Goswami, and K. Krishnakumar, 2010: Indian summer monsoon precipitation climatology in a high-resolution regional climate model: Impact of cumulus parameterization schemes on systematic biases. Wea. Forecasting, 25, 369387, https://doi.org/10.1175/2009WAF2222320.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nakanishi, M., and H. Niino, 2009: Development of an improved turbulence closure model for the atmospheric boundary layer. J. Meteor. Soc. Japan, 87, 895912, https://doi.org/10.2151/jmsj.87.895.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Neelin, J., 2007: Moist dynamics of tropical convection zones in monsoons, teleconnections, and global warming. The Global Circulation of the Atmosphere, T. Schneider and A. H. Sobel, Eds., Princeton University Press, 267–301.

  • Nie, J., W. Boos, and Z. Kuang, 2010: Observational evaluation of a convective quasi-equilibrium view of monsoons. J. Climate, 23, 44164428, https://doi.org/10.1175/2010JCLI3505.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Niu, G.-Y., and Coauthors, 2011: The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements. J. Geophys. Res., 116, D12109, https://doi.org/10.1029/2010JD015139.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pielke, R. A., 2001: Influence of the spatial distribution of vegetation and soils on the prediction of cumulus convective rainfall. Rev. Geophys., 39, 151177, https://doi.org/10.1029/1999RG000072.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Prive, N. C., and R. A. Plumb, 2007a: Monsoon dynamics with interactive forcing. Part I: Axisymmetric studies. J. Atmos. Sci., 64, 14171430, https://doi.org/10.1175/JAS3916.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Prive, N. C., and R. A. Plumb, 2007b: Monsoon dynamics with interactive forcing. Part II: Impact of eddies and asymmetric geometries. J. Atmos. Sci., 64, 14311442, https://doi.org/10.1175/JAS3917.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Raju, A., A. Parekh, J. S. Chowdary, and C. Gnanaseelan, 2015: Assessment of the Indian summer monsoon in the WRF regional climate model. Climate Dyn., 44, 30773100, https://doi.org/10.1007/s00382-014-2295-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Raju, P. V. S., R. Bhatla, M. Almazroui, and M. Assiri, 2015: Performance of convection schemes on the simulation of summer monsoon features over the South Asia CORDEX domain using RegCM-4.3. Int. J. Climatol., 35, 46954706, https://doi.org/10.1002/joc.4317.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roxy, M. K., K. Ritika, P. Terray, and S. Masson, 2014: The curious case of Indian Ocean warming. J. Climate, 27, 85018509, https://doi.org/10.1175/JCLI-D-14-00471.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roxy, M. K., K. Ritika, P. Terray, R. Murtugudde, K. Ashok, and B. N. Goswami, 2015: Drying of Indian subcontinent by rapid Indian Ocean warming and a weakening land–sea thermal gradient. Nat. Commun., 6, 7423, https://doi.org/10.1038/ncomms8423.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roxy, M. K., S. Ghosh, A. Pathak, R. Athulya, M. Mujumdar, R. Murtugudde, P. Terray, and M. Rajeevan, 2017: A threefold rise in widespread extreme rain events over central India. Nat. Commun., 8, 708, https://doi.org/10.1038/s41467-017-00744-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rupa Kumar, K., A. K. Sahai, K. Krishna Kumar, S. K. Patwardhan, P. K. Mishra, J. V. Revadekar, K. Kamala, and G. B. Pant, 2006: High-resolution climate change scenarios for India for the 21st century. Curr. Sci., 90, 334345.

    • Search Google Scholar
    • Export Citation
  • Shi, Y., 2010: A high resolution climate change simulation of the 21st century over East Asia by RegCM3 (in Chinese). Ph.D. dissertation, Chinese Academy of Sciences, 118 pp.

  • Shi, Y., X. J. Gao, D. F. Zhang, and F. Giorgi, 2011: Climate change over the Yarlung Zangbo–Brahmaputra River Basin in the 21st century as simulated by a high resolution regional climate model. Quat. Int., 244, 159168, https://doi.org/10.1016/j.quaint.2011.01.041.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., and J. B. Klemp, 2008: A time-split nonhydrostatic atmospheric model for weather research and forecasting applications. J. Comput. Phys., 227, 34653485, https://doi.org/10.1016/j.jcp.2007.01.037.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Srinivas, C. V., D. Hariprasad, D. V. B. Rao, Y. Anjaneyulu, R. Baskaran, and B. Venkatraman, 2013: Simulation of the Indian summer monsoon regional climate using advanced research WRF model. Int. J. Climatol., 33, 11951210, https://doi.org/10.1002/joc.3505.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Srinivas, C. V., D. V. Bhaskar Rao, D. Hari Prasad, K. B. R. R. Hari Prasad, Y. R. Baskaran, and B. Venkatraman, 2015: A study on the influence of the land surface processes on the southwest monsoon simulations using a regional climate model. Pure Appl. Geophys., 172, 27912811, https://doi.org/10.1007/s00024-014-0905-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tewari, M., and Coauthors, 2004: Implementation and verification of the unified Noah land surface model in the WRF Model. 20th Conf. on Weather Analysis and Forecasting/16th Conf. on Numerical Weather Prediction, Seattle, WA, Amer. Meteor. Soc., 14.2a, https://ams.confex.com/ams/pdfpapers/69061.pdf.

  • Tiedtke, M., 1989: A comprehensive mass flux scheme for cumulus parameterization in large-scale models. Mon. Wea. Rev., 117, 17791800, https://doi.org/10.1175/1520-0493(1989)117<1779:ACMFSF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tiwari, P. R., S. C. Kar, U. C. Mohanty, S. Dey, S. Kumari, P. Sinha, P. V. S. Raju, and M. S. Shekhar, 2016: Simulations of tropical circulation and winter precipitation over north India: An application of a tropical band version of Regional Climate Model (RegT-Band). Pure Appl. Geophys., 173, 657674, https://doi.org/10.1007/s00024-015-1102-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Varikoden, H., M. Mujumdar, J. V. Revadekar, K. P. Sooraj, M. V. S. Ramarao, J. Sanjay, and R. Krishnan, 2018: Assessment of regional downscaling simulations for long term mean, excess and deficit Indian Summer Monsoons. Global Planet. Change, 162, 2838, https://doi.org/10.1016/j.gloplacha.2017.12.002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Verma, R. R., T. K. Srivastava, and P. Singh, 2018: Climate change impacts on rainfall and temperature in sugarcane growing Upper Gangetic Plains of India. Theor. Appl. Climatol., 135, 279292, https://doi.org/10.1007/s00704-018-2378-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Webster, P. J., V. O. Magaña, T. N. Palmer, J. Shukla, R. A. Tomas, M. Yanai, and T. Yasunari: 1998: Monsoons: Processes, predictability, and the prospects for prediction. J. Geophys. Res., 103, 14 45114 510, https://doi.org/10.1029/97JC02719.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wentz, F. J., 1997: A well-calibrated ocean algorithm for special sensor microwave/imager. J. Geophys. Res., 102, 87038718, https://doi.org/10.1029/96JC01751.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xie, S. P., H. Xu, N. H. Saji, and Y. Wang, 2006: Role of narrow mountains in large-scale organization of Asian monsoon convection. J. Climate, 19, 34203429, https://doi.org/10.1175/JCLI3777.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yasunari, T., K. Saito, and K. Takata, 2006: Relative roles of large-scale orography and land surface processes in the global hydroclimate. Part I: Impacts on monsoon systems and the tropics. J. Hydrometeor., 7, 626641, https://doi.org/10.1175/JHM515.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yeh, T.-C., 1950: The circulation of high troposphere over China in winter of 1945–46. Tellus, 2, 173183, https://doi.org/10.3402/tellusa.v2i3.8548.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, D.-F., X.-J. Gao, H.-Z. Bai, and D.-L. Li, 2005: Simulation of climate over Qinghai-Xizang Plateau utilizing RegCM3 (in Chinese). Plateau Meteor., 24, 714720.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 812 319 11
PDF Downloads 613 106 3