The Role of Unresolved Clouds on Short-Range Global Horizontal Irradiance Predictability

Pedro A. Jiménez Research Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado

Search for other papers by Pedro A. Jiménez in
Current site
Google Scholar
PubMed
Close
,
Stefano Alessandrini Research Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado

Search for other papers by Stefano Alessandrini in
Current site
Google Scholar
PubMed
Close
,
Sue Ellen Haupt Research Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado

Search for other papers by Sue Ellen Haupt in
Current site
Google Scholar
PubMed
Close
,
Aijun Deng Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania

Search for other papers by Aijun Deng in
Current site
Google Scholar
PubMed
Close
,
Branko Kosovic Research Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado

Search for other papers by Branko Kosovic in
Current site
Google Scholar
PubMed
Close
,
Jared A. Lee Research Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado

Search for other papers by Jared A. Lee in
Current site
Google Scholar
PubMed
Close
, and
Luca Delle Monache Research Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado

Search for other papers by Luca Delle Monache in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

The shortwave radiative impacts of unresolved cumulus clouds are investigated using 6-h ensemble simulations performed with the WRF-Solar Model and high-quality observations over the contiguous United States for a 1-yr period. The ensembles use the stochastic kinetic energy backscatter scheme (SKEBS) to account for implicit model uncertainty. Results indicate that parameterizing the radiative effects of both deep and shallow cumulus clouds is necessary to largely reduce (55%) a systematic overprediction of the global horizontal irradiance. Accounting for the model’s effective resolution is necessary to mitigate the underdispersive nature of the ensemble and provide meaningful quantification of the short-range prediction uncertainties.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Corresponding author address: Pedro A. Jiménez, Research Applications Laboratory, National Center for Atmospheric Research, 3450 Mitchell Ln., Boulder, CO 80301. E-mail: jimenez@ucar.edu

Abstract

The shortwave radiative impacts of unresolved cumulus clouds are investigated using 6-h ensemble simulations performed with the WRF-Solar Model and high-quality observations over the contiguous United States for a 1-yr period. The ensembles use the stochastic kinetic energy backscatter scheme (SKEBS) to account for implicit model uncertainty. Results indicate that parameterizing the radiative effects of both deep and shallow cumulus clouds is necessary to largely reduce (55%) a systematic overprediction of the global horizontal irradiance. Accounting for the model’s effective resolution is necessary to mitigate the underdispersive nature of the ensemble and provide meaningful quantification of the short-range prediction uncertainties.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Corresponding author address: Pedro A. Jiménez, Research Applications Laboratory, National Center for Atmospheric Research, 3450 Mitchell Ln., Boulder, CO 80301. E-mail: jimenez@ucar.edu
Save
  • Alapaty, K., J. A. Herwehe, T. L. Otte, C. G. Nolte, O. Russell Bullock, M. S. Mallard, J. S. Kain, and J. Dudhia, 2012: Introducing subgrid-scale cloud feedbacks to radiation for regional meteorological and climate modeling. Geophys. Res. Lett., 39, L24809, doi:10.1029/2012GL054031.

    • Search Google Scholar
    • Export Citation
  • Anderson, J. L., 1996: A method for producing and evaluating probabilistic forecasts from ensemble model integrations. J. Climate, 9, 15181530, doi:10.1175/1520-0442(1996)009<1518:AMFPAE>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Augustine, J. A., J. J. DeLuisi, and C. N. Long, 2000: SURFRAD: A national surface radiation budget network for atmospheric research. Bull. Amer. Meteor. Soc., 81, 23412357, doi:10.1175/1520-0477(2000)081<2341:SANSRB>2.3.CO;2.

    • Search Google Scholar
    • Export Citation
  • Augustine, J. A., G. B. Hodges, C. R. Cornwall, J. J. Michalsky, and C. I. Medina, 2005: An update on SURFRAD—The GCOS surface radiation budget network for the continental United States. J. Atmos. Oceanic Technol., 22, 14601472, doi:10.1175/JTECH1806.1.

    • Search Google Scholar
    • Export Citation
  • Benjamin, S. G., G. A. Grell, J. M. Brown, and T. G. Smirnova, 2004: Mesoscale weather prediction with the RUC hybrid isentropic-terrain-following coordinate model. Mon. Wea. Rev., 132, 473494, doi:10.1175/1520-0493(2004)132<0473:MWPWTR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Benjamin, S. G., S. S. Weygandt, C. R. Alexander, J. M. Brown, T. Smirnova, P. Hofmann, E. P. James, and G. DiMego, 2011: NOAA’s hourly-updated 3 km HRRR and RUC/Rapid Refresh— Recent (2010) and upcoming changes toward improving weather guidance for air-traffic management. Second Aviation, Range, and Aerosopace Meterorology Special Symp. on Weather-Air Traffic Management Integration, Seattle, WA, Amer. Meteor. Soc., 3.2. [Available online at https://ams.confex.com/ams/91Annual/webprogram/Paper185659.html.]

  • Berg, L. K., W. I. Gustafson Jr., E. I. Kassianov, and L. Deng, 2013: Evaluation of a modified scheme for shallow convection: Implementation of CuP and case studies. Mon. Wea. Rev., 141, 134147, doi:10.1175/MWR-D-12-00136.1.

    • Search Google Scholar
    • Export Citation
  • Berner, J., G. Shutts, M. Leutbecher, and T. Palmer, 2009: A spectral stochastic kinetic energy backscatter scheme and its impact on flow-depended predictability in the ECMWF ensemble prediction system. J. Atmos. Sci., 66, 603626, doi:10.1175/2008JAS2677.1.

    • Search Google Scholar
    • Export Citation
  • Berner, J., S.-Y. Ha, J. P. Hacker, A. Fournier, and C. Snyder, 2011: Model uncertainty in a mesoscale ensemble prediction system: Stochastic versus multiphysics representations. Mon. Wea. Rev., 139, 19721995, doi:10.1175/2010MWR3595.1.

    • Search Google Scholar
    • Export Citation
  • Berner, J., K. Fossell, S.-Y. Ha, J. P. Hacker, and C. Snyder, 2015: Increasing the skill of probabilistic forecasts: Understanding performance improvements from model-error representations. Mon. Wea. Rev., 143, 12951320, doi:10.1175/MWR-D-14-00091.1.

    • Search Google Scholar
    • Export Citation
  • Buizza, R., D. S. Richardson, and T. N. Palmer, 2003: Benefits of increased resolution in the ECMWF ensemble system and comparison with poor-man’s ensembles. Quart. J. Roy. Meteor. Soc., 129, 12691288, doi:10.1256/qj.02.92.

    • Search Google Scholar
    • Export Citation
  • Deng, A., B. J. Gaudet, J. Dudhia, and K. Alapaty, 2014: Implementation and evaluation of a new shallow convection scheme in WRF. 26th Conf. on Weather Analysis and Forecasting/22nd Conf. on Numerical Weather Prediction, Atlanta, GA, Amer. Meteor. Soc., 12.5. [Available online at https://ams.confex.com/ams/94Annual/webprogram/Paper236925.html.]

  • Diagne, M., M. David, P. Lauret, J. Boland, and N. Schmutz, 2013: Review of solar irradiance forecasting methods and a proposition for small-scale insular grids. Renewable Sustainable Energy Rev., 27, 6576, doi:10.1016/j.rser.2013.06.042.

    • Search Google Scholar
    • Export Citation
  • Durran, D. R., and M. Gingrich, 2014: Atmospheric predictability: Why butterflies are not important. J. Atmos. Sci., 71, 24762488 doi:10.1175/JAS-D-14-0007.1.

    • Search Google Scholar
    • Export Citation
  • Eckel, F. A., and C. F. Mass, 2005: Aspect of effective mesoscale, short-range ensemble forecasting. Wea. Forecasting, 20, 328350, doi:10.1175/WAF843.1.

    • Search Google Scholar
    • Export Citation
  • Grell, G. A., and S. Freitas, 2014: A scale and aerosol aware stochastic convective parameterization for weather and air quality modeling. Atmos. Chem. Phys., 14, 52335250, doi:10.5194/acp-14-5233-2014.

    • Search Google Scholar
    • Export Citation
  • Herwehe, J., K. Alapaty, T. Spero, and C. G. Nolte, 2014: Increasing the credibility of regional climate simulations by introducing subgrid-scale cloud-radiation interactions. J. Geophys. Res. Atmos., 119, 53175330, doi:10.1002/2014JD021504.

    • Search Google Scholar
    • Export Citation
  • Hicks, B. B., J. J. DeLuisi, and D. R. Matt, 1996: The NOAA Integrated Surface Irradiance Study (ISIS): A new surface radiation monitoring program. Bull. Amer. Meteor. Soc., 77, 28572864, doi:10.1175/1520-0477(1996)077<2857:TNISIS>2.0.CO;2.

    • Search Google Scholar
    • 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, doi:10.1029/2008JD009944.

    • Search Google Scholar
    • Export Citation
  • Jiménez, P. A., and Coauthors, 2016: WRF-Solar: Description and clear-sky assessment of an augmented NWP model for solar power prediction. Bull. Amer. Meteor. Soc., 97, 12491264, doi:10.1175/BAMS-D-14-00279.1.

    • Search Google Scholar
    • Export Citation
  • Lara-Fanego, V., J. A. Ruiz-Arias, D. Pozo-Vazquez, F. J. Santos-Alamillos, and J. Tovar-Pescador, 2012: Evaluation of the WRF model solar irradiance forecasts in Andalusia (southern Spain). Sol. Energy, 86, 22002217, doi:10.1016/j.solener.2011.02.014.

    • Search Google Scholar
    • Export Citation
  • Lorenz, E. N., 1969: The predictability of a flow which possess many scales of motion. Tellus, 21A, 289307, doi:10.1111/j.2153-3490.1969.tb00444.x.

    • Search Google Scholar
    • Export Citation
  • Mathiesen, P., and J. Kleissl, 2011: Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States. Sol. Energy, 85, 967977, doi:10.1016/j.solener.2011.02.013.

    • 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, doi:10.2151/jmsj.87.895.

    • Search Google Scholar
    • Export Citation
  • Raftery, A. E., T. Gneiting, F. Balabdaoui, and M. Polakowski, 2005: Using Bayesian model averaging to calibrate forecast ensembles. Mon. Wea. Rev., 133, 11551174, doi:10.1175/MWR2906.1.

    • Search Google Scholar
    • Export Citation
  • Roesch, A., M. Wild, A. Ohmura, E. G. Dutton, C. N. Long, and T. Zhang, 2011: Assessment of BSRN radiation records for the computation of monthly means. Atmos. Meas. Tech., 4, 339354, doi:10.5194/amt-4-339-2011.

    • Search Google Scholar
    • Export Citation
  • Rotunno, R., and C. Snyder, 2008: A generalization of Lorenz’s model for the predictability of flows with many scales of motion. J. Atmos. Sci., 65, 10631076, doi:10.1175/2007JAS2449.1.

    • Search Google Scholar
    • Export Citation
  • Ruiz-Arias, J. A., J. Dudhia, F. J. Santos-Alamillos, and D. Pozo-Vázquez, 2013: Surface clear-sky shortwave radiative closure intercomparisons in the Weather Research and Forecasting model. J. Geophys. Res. Atmos., 118, 99019913, doi:10.1002/jgrd.50778.

    • Search Google Scholar
    • Export Citation
  • Ruiz-Arias, J. A., J. Dudhia, and C. A. Gueymard, 2014: A simple parameterization of the short-wave aerosol optical properties for surface direct and diffuse irradiances assessment in a numerical weather model. Geosci. Model Dev., 7, 11591174, doi:10.5194/gmd-7-1159-2014.

    • Search Google Scholar
    • Export Citation
  • Ruiz-Arias, J. A., C. Arbizu-Barrena, F. J. Santos-Alamillos, J. Tovar-Pescador, and D. Pozo-Vázquez, 2016: Assessing the surface solar radiation budget in the WRF Model: A spatiotemporal analysis of the bias and its causes. Mon. Wea. Rev., 144, 703711, doi:10.1175/MWR-D-15-0262.1

    • Search Google Scholar
    • Export Citation
  • Shutts, G., 2005: A kinetic energy backscatter algorithm for use in ensemble prediction systems. Quart. J. Roy. Meteor. Soc., 131, 30793102, doi:10.1256/qj.04.106.

    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., 2004: Evaluating mesoscale NWP models using kinetic energy spectra. Mon. Wea. Rev., 132, 30193032, doi:10.1175/MWR2830.1.

    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., and Coauthors, 2008: A description of the Advanced Research WRF version 3. NCAR Tech. Note NCAR/TN-475+STR, 113 pp., doi:10.5065/D68S4MVH.

  • Stensrud, D. J., 2007: Parameterization Schemes: Keys to Understanding Numerical Weather Prediction Models. Cambridge University Press, 478 pp.

  • Thompson, D., J. J. Kennedy, J. M. Wallace, and P. D. Jones, 2008: A large discontinuity in the mid-twentieth century observed global-mean surface temperature. Nature, 453, 646649, doi:10.1038/nature06982.

    • Search Google Scholar
    • Export Citation
  • Weygandt, S., and Coauthors, 2011: The Rapid Refresh—Replacememnt for the RUC, pre-implementation development and evaluation. 24th Conf. on Weather and Forecasting/20th Conf. on Numerical Weather Prediction, Seatle, WA, Amer. Meteor. Soc., 12B.1. [Available online at https://ams.confex.com/ams/91Annual/webprogram/Paper183027.html.]

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 905 404 20
PDF Downloads 435 189 12