• Chang, E. K. M., 2009: Diabatic and orographic forcing of northern winter stationary waves and storm tracks. J. Climate, 22, 670688.

  • Collins, W. D., and Coauthors, 2004: Description of the NCAR Community Atmosphere Model (CAM 3.0). NCAR Tech. Note NCAR/TN-464+STR, 210 pp. [Available online at http://www.cesm.ucar.edu/models/atm-cam/docs/description/.]

    • Search Google Scholar
    • Export Citation
  • Collins, W. D., and Coauthors, 2006: The formulation and atmospheric simulation of the Community Atmospheric Model version 3 (CAM3). J. Climate, 19, 21442161.

    • Search Google Scholar
    • Export Citation
  • Held, I. M., , M. Ting, , and H. Wang, 2002: Northern winter stationary waves: Theory and modeling. J. Climate, 15, 21252144.

  • Kiehl, J. T., , J. J. Hack, , G. B. Bonan, , B. A. Boville, , D. L. Williamson, , and P. J. Rasch, 1998: The National Center for Atmospheric Research Community Climate Model: CCM3. J. Climate, 11, 11311149.

    • Search Google Scholar
    • Export Citation
  • Park, H.-S., , J. C. H. Chiang, , and S.-W. Son, 2010: The role of the central Asian mountains on the midwinter suppression of North Pacific storminess. J. Atmos. Sci., 67, 37063720.

    • Search Google Scholar
    • Export Citation
  • Zhang, Y., , and I. M. Held, 1999: A linear stochastic model of a GCM’s midlatitude storm tracks. J. Atmos. Sci., 56, 34163435.

  • View in gallery

    Orography over central Asia used in the four different experiments: (a) MN100, (b) MN70, (c) MN40, and (d) MN05. Mountains higher than 500 m are shaded.

  • View in gallery

    (a) The 300-hPa eddy streamfunction for MN100. (b)–(d) Anomalous eddy streamfunction calculated from the differences between MN100 and others: (b) MN100 − MN70, (c) MN100 − MN40, and (d) MN100 − MN05. Contour interval is 3 × 106 m2 s−1.

  • View in gallery

    (a) Anomalous 300-hPa storminess (shading, interval −10 m; dotted line shows −5-m contour), calculated from the differences between MN100 and MN40. The contour lines indicate climatological mean storminess for MN40. (b) As in (a), but for the MN05 experiment. (c) As in (b), but for anomalous 300-hPa filtered EKE (shading interval −15 m2 s−2).

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 22 22 2
PDF Downloads 13 13 1

Comments on “The Role of the Central Asian Mountains on the Midwinter Suppression of North Pacific Storminess”

View More View Less
  • 1 School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, New York
  • | 2 Atmospheric Sciences Division, Brookhaven National Laboratory, Upton, New York
© Get Permissions
Full access

Corresponding author address: Edmund K. M. Chang, School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY 11794-5000. E-mail: kmchang@notes.cc.sunysb.edu

The original article that was the subject of this comment/reply can be found at http://journals.ametsoc.org/doi/abs/10.1175/2010JAS3349.1.

Corresponding author address: Edmund K. M. Chang, School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY 11794-5000. E-mail: kmchang@notes.cc.sunysb.edu

The original article that was the subject of this comment/reply can be found at http://journals.ametsoc.org/doi/abs/10.1175/2010JAS3349.1.

In a recent study, Park et al. (2010) conducted experiments using an atmospheric general circulation model (AGCM) to study the impact of the central Asian mountains on Pacific storm-track activity. Their results suggested that “the presence of the central Asian mountains suppresses the North Pacific storminess by 20%–30% during boreal winter” and can “amplify stationary waves and effectively weaken the high-frequency transient eddy kinetic energy in boreal winter.” We are intrigued by such strong sensitivity of the winter storm track and stationary waves to the central Asian mountains, since in a previous study (Chang 2009) we have conducted numerical experiments to examine the impact of mountains on Northern Hemisphere winter storm tracks and stationary waves by removing all mountains and found apparently weaker impacts than those found by Park et al. (2010). Since the configuration of the experiments examined by Chang (2009) is different from those presented in Park et al., we have performed some experiments similar to those discussed in Park et al. to more directly compare our results to theirs.

The AGCM used in this study is the Community Atmospheric Model version 3.1 (CAM3.1; see Collins et al. 2006), run at a resolution of T42 in the horizontal, with 26 hybrid sigma levels in the vertical. Compared to the model used by Park et al. [version 3 of the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM3) run at T42 and 18 levels; see Kiehl et al. 1998], the model used in this study has updated physics and higher vertical resolution. Major changes in model physics from CCM3 to CAM3 are described in Collins et al. (2004). All experiments are run with climatological SST as a lower boundary condition.

Park et al. (2010) conducted a series of experiments to examine the impacts of the Altai-Sayan Mountains on the Pacific storm track. Their control experiment (M100) is run with full orography. They then conducted sensitivity experiments by systematically reducing the orography over central Asia (see their Table 1 and Fig. 1). The experiments that they called M75 and M50 have the Altai-Sayan mountains largely removed, with part of the Tibetan Plateau also removed in the latter case, and their M20 experiment has most of the Tibetan Plateau reduced. We have conducted a similar series of experiments, with the orography used in our four experiments shown in our Fig. 1. Comparing our orography to theirs (see their Fig. 1), our reductions are slightly more aggressive (with more of the mountains removed); hence we named our experiments MN100 (control with full orography), MN70, MN40, and MN05, respectively (see Fig. 1). As in Park et al. (2010), over regions where the orography is reduced, the subgrid-scale variability (standard deviation) in orography (used in gravity wave drag parameterization) is also reduced by the same ratio. Note that outside of central Asia the orography is unchanged.

Fig. 1.
Fig. 1.

Orography over central Asia used in the four different experiments: (a) MN100, (b) MN70, (c) MN40, and (d) MN05. Mountains higher than 500 m are shaded.

Citation: Journal of the Atmospheric Sciences 68, 11; 10.1175/JAS-D-11-021.1

Since the results of Park et al. (2010) suggested that the central Asian mountains have the largest impacts on the Northern Hemisphere (NH) storm tracks during midwinter, we will focus on this season here. To obtain a longer time series for midwinter without having to run the experiments for many decades, we have conducted persistent January forcing experiments. Previous studies (e.g., Zhang and Held 1999; Chang 2009) have shown that persistent forcing experiments using AGCMs can reproduce NH winter climate very well, and Zhang and Held (1999) also showed that the midwinter suppression in Pacific storm-track activity can be reproduced in persistent forcing experiments run with forcing from the different months. Each of the four experiments is run for 15 yr under persistent 15 January insolation and SST forcings, with data from the final 10 yr (or 120 months) analyzed to examine the sensitivity of the Northern Hemisphere winter climate to differences in orography.

The response of the winter stationary waves to changes in orography is shown in Fig. 2 (this figure should be compared to Fig. 8 of Park et al). The stationary wave response is represented by the zonal asymmetrical (or eddy) part of the 300-hPa streamfunction. The stationary waves simulated in the control experiment are shown in Fig. 2a. This pattern is very similar to that shown in Fig. 8a of Park et al. (2010), but the amplitude is a bit weaker here. However, our stationary wave amplitude agrees better with observed January stationary waves derived from National Centers for Environmental prediction (NCEP)–NCAR reanalysis (e.g., see Fig. 1a of Held et al. 2002).

Fig. 2.
Fig. 2.

(a) The 300-hPa eddy streamfunction for MN100. (b)–(d) Anomalous eddy streamfunction calculated from the differences between MN100 and others: (b) MN100 − MN70, (c) MN100 − MN40, and (d) MN100 − MN05. Contour interval is 3 × 106 m2 s−1.

Citation: Journal of the Atmospheric Sciences 68, 11; 10.1175/JAS-D-11-021.1

Examining the responses of the stationary waves to changes in orography, our results are consistent with those of Park et al. (2010) in that the central Asian mountains clearly enhance the stationary waves, especially the part of the wave spreading from Asia across the Pacific into western North America. However, it is clear that the amplitudes of the responses in our experiments are significantly smaller than those shown in Fig. 8 of Park et al. For example, in their M50 experiment, the negative center over East Asia is reduced by over 18 × 106 m2 s−1 (compared to a climatological amplitude of about −24 × 106 m2 s−1), while in all of our experiments, even the one with most of Tibet removed (MN05), the reduction never exceeds half that value.

The storm-track response to changes in orography is shown in Fig. 3 (this should be compared to Fig. 4a of Park et al.). Similar to Park et al., to represent “storminess,” we use 8-day high-pass filtered standard deviation of 300-hPa geopotential height. In Fig. 3a, the differences between the control and MN40 experiments are shown by shades (with the −5-m difference contour shown by dotted contours), while the storm tracks simulated by the MN40 experiment are shown by the solid contours. We have used the same shade interval (10 m) and contour interval as those used in Park et al. (2010) so that our results can be directly compared to theirs. Comparing our Fig. 3a to their Fig. 4a, it is clear that in both experiments, the central Asian mountains strongly suppress storm-track activity locally. However, downstream over eastern Asia, the Pacific, North America, and the Atlantic, changes in orography generate much weaker responses in our experiments than in those conducted by Park et al. (2010). In Fig. 3b, the storm-track response to the MN05 experiment is shown. Even after removing nearly the entire Tibetan Plateau, the increase in storminess never exceeds 15 m in amplitude over the Pacific east of 170°E, much less than the over 30-m increase in amplitude found by Park et al. (2010) for their M50 experiment.

Fig. 3.
Fig. 3.

(a) Anomalous 300-hPa storminess (shading, interval −10 m; dotted line shows −5-m contour), calculated from the differences between MN100 and MN40. The contour lines indicate climatological mean storminess for MN40. (b) As in (a), but for the MN05 experiment. (c) As in (b), but for anomalous 300-hPa filtered EKE (shading interval −15 m2 s−2).

Citation: Journal of the Atmospheric Sciences 68, 11; 10.1175/JAS-D-11-021.1

As in Park et al. (2010), we have also computed the storm-track response in terms of 300-hPa filtered eddy kinetic energy (EKE). The results for the MN05 experiment are shown in Fig. 3c. Consistent with the results for storminess (Fig. 3b), the EKE is strongly suppressed near the mountains, but the reduction is significantly less away from them. Compared to Fig. 9a in Park et al. (2010),1 over the central and eastern Pacific, the response in our experiments is clearly much weaker even with much more of Tibet removed.

Overall, our results suggest that while the central Asian mountains do enhance the stationary waves and suppress storm-track activity during midwinter, the sensitivity of both to the mountains may be much less than what the results of Park et al. (2010) suggest. Our results suggest that while the central Asian mountains may indeed contribute to the midwinter suppression of the Pacific storm track, merely removing these mountains is unlikely to remove the suppression, and other physical mechanisms are still needed to help explain this phenomenon.

Currently, it is not clear why our results differ from those of Park et al. (2010). Possibilities include differences in model physics as well as differences in vertical resolution. Statistics may also play a small role, as Park et al. (2010) only used data from 18 winter seasons, while we analyzed 120 months of data. If we replot Fig. 2 using only 18 months of data, the amplitude of the differences between the control and sensitivity experiments would have been larger in some of those plots. However, splitting our 120 months into six 18-month periods, we did not find any period during which the change in stationary waves is as large as those shown in Fig. 8 of Park et al. With 120 months of data (see Fig. 2), the change in stationary waves (at least over Asia and the western Pacific) is found to become systematically larger as more of the mountains are removed, whereas with 18 months of data, such systematic increase is not always observed, suggesting that 18 seasons is probably not long enough to quantitatively characterize the response.

Our results suggest that model-simulated storm-track and stationary wave responses to changes in orographic forcing appear to be very sensitive to the model used. Further studies, perhaps using multimodel ensembles, as well as efforts to understand what causes these large model differences, will be needed to better quantify the impacts of the central Asian mountains on Northern Hemisphere winter climate.

Acknowledgments

One of us (EC) is supported by NSF Grant ATM0757250. Most of the CAM runs are conducted on the NCAR Bluefire supercomputer.

REFERENCES

  • Chang, E. K. M., 2009: Diabatic and orographic forcing of northern winter stationary waves and storm tracks. J. Climate, 22, 670688.

  • Collins, W. D., and Coauthors, 2004: Description of the NCAR Community Atmosphere Model (CAM 3.0). NCAR Tech. Note NCAR/TN-464+STR, 210 pp. [Available online at http://www.cesm.ucar.edu/models/atm-cam/docs/description/.]

    • Search Google Scholar
    • Export Citation
  • Collins, W. D., and Coauthors, 2006: The formulation and atmospheric simulation of the Community Atmospheric Model version 3 (CAM3). J. Climate, 19, 21442161.

    • Search Google Scholar
    • Export Citation
  • Held, I. M., , M. Ting, , and H. Wang, 2002: Northern winter stationary waves: Theory and modeling. J. Climate, 15, 21252144.

  • Kiehl, J. T., , J. J. Hack, , G. B. Bonan, , B. A. Boville, , D. L. Williamson, , and P. J. Rasch, 1998: The National Center for Atmospheric Research Community Climate Model: CCM3. J. Climate, 11, 11311149.

    • Search Google Scholar
    • Export Citation
  • Park, H.-S., , J. C. H. Chiang, , and S.-W. Son, 2010: The role of the central Asian mountains on the midwinter suppression of North Pacific storminess. J. Atmos. Sci., 67, 37063720.

    • Search Google Scholar
    • Export Citation
  • Zhang, Y., , and I. M. Held, 1999: A linear stochastic model of a GCM’s midlatitude storm tracks. J. Atmos. Sci., 56, 34163435.

1

The EKE values (contours) shown in Fig. 3c appear to be much less than those shown in Fig. 9a of Park et al. (2010). However, note that in our control experiment (MN100), the peak EKE values in the eastern Pacific are only slightly smaller than those computed based on 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) data.

Save