Editorial Type:
Article
Article Type:
Research Article

Evaluation of the AMPS Boundary Layer Simulations on the Ross Ice Shelf with Tower Observations

Jonathan D. Wille Polar Meteorology Group, Byrd Polar and Climate Research Center, The Ohio State University, Columbus, Ohio

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David H. Bromwich Polar Meteorology Group, Byrd Polar and Climate Research Center, The Ohio State University, Columbus, Ohio
Atmospheric Sciences Program, Department of Geography, The Ohio State University, Columbus, Ohio

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Melissa A. Nigro Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado

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John J. Cassano Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado
Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, Colorado

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Marian Mateling Antarctic Meteorological Research Center, Space Science and Engineering Center, University of Wisconsin–Madison, Madison, Wisconsin
Department of Atmospheric and Oceanic Sciences, University of Wisconsin–Madison, Madison, Wisconsin

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Matthew A. Lazzara Antarctic Meteorological Research Center, Space Science and Engineering Center, University of Wisconsin–Madison, Madison, Wisconsin
Department of Physical Sciences, School of Arts and Sciences, Madison Area Technical College, Madison, Wisconsin

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Sheng-Hung Wang Polar Meteorology Group, Byrd Polar and Climate Research Center, The Ohio State University, Columbus, Ohio

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Print Publication:
01 Nov 2016
DOI:
https://doi.org/10.1175/JAMC-D-16-0032.1
Page(s):
2349–2367
Restricted access

Abstract

Flight operations in Antarctica rely on accurate weather forecasts aided by the numerical predictions primarily produced by the Antarctic Mesoscale Prediction System (AMPS) that employs the polar version of the Weather Research and Forecasting (Polar WRF) Model. To improve the performance of the model’s Mellor–Yamada–Janjić (MYJ) planetary boundary layer (PBL) scheme, this study examines 1.5 yr of meteorological data provided by the 30-m Alexander Tall Tower! (ATT) automatic weather station on the western Ross Ice Shelf from March 2011 to July 2012. Processed ATT observations at 10-min intervals from the multiple observational levels are compared with the 5-km-resolution AMPS forecasts run daily at 0000 and 1200 UTC. The ATT comparison shows that AMPS has fundamental issues with moisture and handling stability as a function of wind speed. AMPS has a 10-percentage-point (i.e., RH unit) relative humidity dry bias year-round that is highest when katabatic winds from the Byrd and Mulock Glaciers exceed 15 m s−1. This is likely due to nonlocal effects such as errors in the moisture content of the katabatic flow and AMPS not parameterizing the sublimation from blowing snow. AMPS consistently overestimates the wind speed at the ATT by 1–2 m s−1, in agreement with previous studies that attribute the high wind speed bias to the MYJ scheme. This leads to reduced stability in the simulated PBL, thus affecting the model’s ability to properly simulate the transfer of heat and momentum throughout the PBL.

Byrd Polar and Climate Research Center Contribution 1546.

Corresponding author address: David H. Bromwich, 1090 Carmack Rd. 108 Scott Hall, Columbus, OH 43210. E-mail: bromwich.1@osu.edu

Abstract

Flight operations in Antarctica rely on accurate weather forecasts aided by the numerical predictions primarily produced by the Antarctic Mesoscale Prediction System (AMPS) that employs the polar version of the Weather Research and Forecasting (Polar WRF) Model. To improve the performance of the model’s Mellor–Yamada–Janjić (MYJ) planetary boundary layer (PBL) scheme, this study examines 1.5 yr of meteorological data provided by the 30-m Alexander Tall Tower! (ATT) automatic weather station on the western Ross Ice Shelf from March 2011 to July 2012. Processed ATT observations at 10-min intervals from the multiple observational levels are compared with the 5-km-resolution AMPS forecasts run daily at 0000 and 1200 UTC. The ATT comparison shows that AMPS has fundamental issues with moisture and handling stability as a function of wind speed. AMPS has a 10-percentage-point (i.e., RH unit) relative humidity dry bias year-round that is highest when katabatic winds from the Byrd and Mulock Glaciers exceed 15 m s−1. This is likely due to nonlocal effects such as errors in the moisture content of the katabatic flow and AMPS not parameterizing the sublimation from blowing snow. AMPS consistently overestimates the wind speed at the ATT by 1–2 m s−1, in agreement with previous studies that attribute the high wind speed bias to the MYJ scheme. This leads to reduced stability in the simulated PBL, thus affecting the model’s ability to properly simulate the transfer of heat and momentum throughout the PBL.

Byrd Polar and Climate Research Center Contribution 1546.

Corresponding author address: David H. Bromwich, 1090 Carmack Rd. 108 Scott Hall, Columbus, OH 43210. E-mail: bromwich.1@osu.edu
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  • Acevedo, O. C., L. Mahrt, F. S. Puhales, F. D. Costa, L. E. Medeiros, and G. A. Degrazia, 2016: Contrasting structures between the decoupled and coupled states of the stable boundary layer. Quart. J. Roy. Meteor. Soc., 142, 693–702, doi:10.1002/qj.2693.

    • Search Google Scholar
    • Export Citation

  • Antarctic Mesoscale Prediction System, 2015: Current AMPS configuration. Accessed 4 August 2015. [Available online at http://www2.mmm.ucar.edu/rt/amps/information/configuration/configuration.html.]

  • Barker, D. M., W. Huang, Y.-R. Guo, A. J. Bourgeois, and Q.-N. Xiao, 2004: A three-dimensional variational data assimilation system for MM5: Implementation and initial results. Mon. Wea. Rev., 132, 897–914, doi:10.1175/1520-0493(2004)132<0897:ATVDAS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Bromwich, D. H., A. J. Monaghan, K. W. Manning, and J. G. Powers, 2005: Real-time forecasting for the Antarctic: An evaluation of the Antarctic Mesoscale Prediction System (AMPS). Mon. Wea. Rev., 133, 579–603, doi:10.1175/MWR-2881.1.

    • Search Google Scholar
    • Export Citation

  • Bromwich, D. H., K. M. Hines, and L.-S. Bai, 2009: Development and testing of Polar Weather Research and Forecasting Model: 2. Arctic Ocean. J. Geophys. Res., 114, D08122, doi:10.1029/2008JD010300.

    • Search Google Scholar
    • Export Citation

  • Bromwich, D. H., F. O. Otieno, K. M. Hines, K. W. Manning, and E. Shilo, 2013: Comprehensive evaluation of Polar Weather Research and Forecasting Model performance in the Antarctic. J. Geophys. Res. Atmos., 118, 274–292, doi:10.1029/2012JD018139.

    • Search Google Scholar
    • Export Citation

  • Cassano, J. J., J. E. Box, D. H. Bromwich, L. Li, and K. Steffen, 2001: Evaluation of Polar MM5 simulations of Greenland’s atmospheric circulation. J. Geophys. Res., 106, 33 867–33 890, doi:10.1029/2001JD900044.

    • Search Google Scholar
    • Export Citation

  • Cassano, J. J., M. E. Higgins, and M. W. Seefeldt, 2011: Performance of the Weather Research and Forecasting Model for month-long pan-Arctic simulations. Mon. Wea. Rev., 139, 3469–3488, doi:10.1175/MWR-D-10-05065.1.

    • Search Google Scholar
    • Export Citation

  • Cassano, J. J., M. A. Nigro, and M. A. Lazzara, 2016: Characteristics of the near surface atmosphere over the Ross Ice Shelf, Antarctica. J. Geophys. Res., 121, 3339–3362, doi:10.1029/2005JD006185.

    • Search Google Scholar
    • Export Citation

  • Chou, M.-D., and M. J. Suarez, 1994: Technical report series on global modeling and data assimilation. Vol. 3: An efficient thermal infrared radiation parameterization for use in general circulation models. NASA Tech. Memo. 104606, Vol. 3, 84 pp. [Available online at https://archive.org/details/nasa_techdoc_19950009331.]

  • Fogt, R. L., and D. H. Bromwich, 2008: Atmospheric moisture and cloud cover characteristics forecast by AMPS. Wea. Forecasting, 23, 914–930, doi:10.1175/2008WAF2006100.1.

    • Search Google Scholar
    • Export Citation

  • Genthon, C., D. Six, H. Gallee, P. Grigioni, and A. Pellegrini, 2013: Two years of atmospheric boundary layer observations on a 45-m tower at Dome C on the Antarctic plateau. J. Geophys. Res. Atmos., 118, 3218–3232, doi:10.1002/jgrd.50128.

    • Search Google Scholar
    • Export Citation

  • Hines, K. M., and D. H. Bromwich, 2008: Development and testing of Polar Weather Research and Forecasting (WRF) Model. Part I: Greenland ice sheet meteorology. Mon. Wea. Rev., 136, 1971–1989, doi:10.1175/2007MWR2112.1.

    • Search Google Scholar
    • Export Citation

  • Hines, K. M., D. H. Bromwich, L.-S. Bai, M. Barlage, and A. G. Slater, 2011: Development and testing of Polar WRF. Part III: Arctic land. J. Climate, 24, 26–48, doi:10.1175/2010JCLI3460.1.

    • Search Google Scholar
    • Export Citation

  • Hines, K. M., D. H. Bromwich, L.-S. Bai, C. M. Bitz, J. G. Powers, and K. W. Manning, 2015: Sea ice enhancements to Polar WRF. Mon. Wea. Rev., 143, 2363–2385, doi:10.1175/MWR-D-14-00344.1.

    • Search Google Scholar
    • Export Citation

  • Holtslag, A. A. M., and Coauthors, 2013: Stable atmospheric boundary layers and diurnal cycles: Challenges for weather and climate models. Bull. Amer. Meteor. Soc., 94, 1691–1706, doi:10.1175/BAMS-D-11-00187.1.

    • Search Google Scholar
    • Export Citation

  • Hong, S.-Y., J. Dudhia, and S.-H. Chen, 2004: A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon. Wea. Rev., 132, 103–120, doi:10.1175/1520-0493(2004)132<0103:ARATIM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Hu, X.-M., J. W. Nielsen-Gammon, and F. Zhang, 2010: Evaluation of three planetary boundary layer schemes in the WRF Model. J. Appl. Meteor. Climatol., 49, 1831–1844, doi:10.1175/2010JAMC2432.1.

    • 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, 927–945, doi:10.1175/1520-0493(1994)122<0927:TSMECM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • King, J. C., and J. Turner, 1997: Antarctic Meteorology and Climatology. Cambridge University Press, 290 pp.

  • Lazzara, M. A., J. E. Thom, L. J. Welhouse, L. M. Keller. G. A. Weidner, M. Nigro, and J. J. Cassano, 2011: USAP Antarctic Automatic Weather Station Program status and field report. Sixth Antarctic Meteorological Observation, Modeling, and Forecasting Workshop, Hobart, Australia, Australian Bureau of Meteorology, Paper 1.2. [Available online at http://amrc.ssec.wisc.edu/abstracts/AMOMFW2011-Lazzara-AWS-final.pdf.]

  • Lazzara, M. A., G. A. Weidner, L. M. Keller, J. E. Thom, and J. J. Cassano, 2012: Antarctic Automatic Weather Station program: 30 years of polar observation. Bull. Amer. Meteor. Soc., 93, 1519–1537, doi:10.1175/BAMS-D-11-00015.1.

    • Search Google Scholar
    • Export Citation

  • Liu, Z., and D. H. Bromwich, 1993: Acoustic remote sensing of planetary boundary layer dynamics near Ross Island, Antarctica. J. Appl. Meteor., 32, 1867–1882, doi:10.1175/1520-0450(1993)032<1867:ARSOPB>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Monti, P., H. J. S. Fernando, M. Princevac, W. C. Chan, T. A. Kowalewski, and E. R. Pardyjak, 2002: Observations of flow and turbulence in the nocturnal boundary layer over a slope. J. Atmos. Sci., 59, 2513–2534, doi:10.1175/1520-0469(2002)059<2513:OOFATI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Nigro, M. A., and J. J. Cassano, 2014: Identification of surface wind patterns over the Ross Ice Shelf, Antarctica, using self-organizing maps. Mon. Wea. Rev., 142, 2361–2378, doi:10.1175/MWR-D-13-00382.1.

    • Search Google Scholar
    • Export Citation

  • Parish, T. R., and K. T. Waight III, 1987: The forcing of Antarctic katabatic winds. Mon. Wea. Rev., 115, 2214–2226, doi:10.1175/1520-0493(1987)115<2214:TFOAKW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Parish, T. R., and J. J. Cassano, 2003: The role of katabatic winds on the Antarctic surface wind regime. Mon. Wea. Rev., 131, 317–333, doi:10.1175/1520-0493(2003)131<0317:TROKWO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Powers, J. G., 2009: Performance of the WRF V3.1 polar modifications in an Antarctic severe wind event. Preprints, 10th WRF Users’ Workshop, Boulder, CO, NCAR. [Available online at http://www2.mmm.ucar.edu/wrf/users/workshops/WS2009/abstracts/P3B-26.pdf.]

  • Powers, J. G., K. W. Manning, D. H. Bromwich, J. J. Cassano, and A. M. Cayette, 2012: A decade of Antarctic science support through AMPS. Bull. Amer. Meteor. Soc., 93, 1699–1712, doi:10.1175/BAMS-D-11-00186.1.

    • Search Google Scholar
    • Export Citation

  • Riordan, A. J., 1977: Variations of temperature and air motion in the 0- to 32-meter layer at Plateau Station, Antarctica. Meteorological Studies at Plateau Station, Antarctica. P. C. Dalrymple, et al., Eds., Antarctic Research Series, Vol. 25, Amer. Geophys. Union, 113–127, doi:10.1002/9781118664872.ch8.

  • Russell, J. O. H., D. Parsons, and S. Cavallo, 2014: An evaluation of the Antarctic Mesoscale Prediction System using unique new data from the CONCORDIASI field program. 13th Annual Student Conf., Atlanta, GA, Amer. Meteor. Soc. [Available online at https://ams.confex.com/ams/94Annual/webprogram/Paper242588.html.]

  • Steinhoff, D. F., S. Chaudhuri, and D. H. Bromwich, 2009: A case study of a Ross Ice Shelf airstream event: A new perspective. Mon. Wea. Rev., 137, 4030–4046, doi:10.1175/2009MWR2880.1.

    • Search Google Scholar
    • Export Citation

  • Sterk, H. A. M., G. J. Steeneveld, and A. A. M. Holtslag, 2013: The role of snow-surface coupling, radiation, and turbulent mixing in modeling a stable boundary layer over Arctic sea ice. J. Geophys. Res., 118, 1199–1217, doi:10.1002/jgrd.50158.

    • Search Google Scholar
    • Export Citation

  • Tastula, E. M., T. Vihma, and E. L Andreas, 2012: Evaluation of Polar WRF from modeling the atmospheric boundary layer over Antarctic sea ice in autumn and winter. Mon. Wea. Rev., 140, 3919–3935, doi:10.1175/MWR-D-12-00016.1.

    • 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. [Available online at https://ams.confex.com/ams/pdfpapers/69061.pdf.]

  • Valkonen, T., T. Vihma, M. M. Johansson, and J. Launiainen, 2014: Atmosphere–sea ice interaction in early summer in the Antarctic: Evaluation and challenges of a regional atmospheric model. Quart. J. Roy. Meteor. Soc., 140, 1536–1551, doi:10.1002/qj.2237.

    • Search Google Scholar
    • Export Citation

  • Vázquez Becerra, G. E., and D. A. Grejner-Brzezinska, 2013: GPS-PWV estimation and validation with radiosonde data and numerical weather prediction model in Antarctica. GPS Solutions, 17 (1), 29–39, doi:10.1007/s10291-012-0258-8.

    • Search Google Scholar
    • Export Citation
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