globalchange  > 气候变化事实与影响
DOI: doi:10.1038/nclimate2783
论文题名:
Causes of change in Northern Hemisphere winter meridional winds and regional hydroclimate
作者: Isla R. Simpson
刊名: Nature Climate Change
ISSN: 1758-767X
EISSN: 1758-6887
出版年: 2015-09-07
卷: Volume:6, 页码:Pages:65;70 (2016)
语种: 英语
英文关键词: Atmospheric science ; Projection and prediction ; Climate and Earth system modelling ; Hydrology
英文摘要:

A critical aspect of human-induced climate change is how it will affect precipitation around the world. Broadly speaking, warming increases atmospheric moisture holding capacity, intensifies moisture transports and makes sub-tropical dry regions drier and tropical and mid-to-high-latitude wet regions wetter1, 2. Extra-tropical precipitation patterns vary strongly with longitude, however, owing to the control exerted by the storm tracks and quasi-stationary highs and lows or stationary waves. Regional precipitation change will, therefore, also depend on how these aspects of the circulation respond. Current climate models robustly predict a change in the Northern Hemisphere (NH) winter stationary wave field that brings wetting southerlies to the west coast of North America, and drying northerlies to interior southwest North America and the eastern Mediterranean3, 4, 5. Here we show that this change in the meridional wind field is caused by strengthened zonal mean westerlies in the sub-tropical upper troposphere, which alters the character of intermediate-scale stationary waves. Thus, a robust and easily understood model response to global warming is the prime cause of these regional wind changes. However, the majority of models probably overestimate the magnitude of this response because of biases in their climatological representation of the relevant waves, suggesting that winter season wetting of the North American west coast will be notably less than projected by the multi-model mean.

Stationary waves arise from longitudinal asymmetries in topography, diabatic heating and transient eddy heat and vorticity fluxes. The character of the forced waves depends not only on these asymmetric forcings, but also on the zonal mean flow and nonlinear wave–wave interaction, with the additional complication that the asymmetric forcings and zonal mean flow are, in turn, affected by the stationary waves6. In the NH winter, climate models predict that stationary wave changes will form an important component of mid-latitude circulation change7, 8, 9 and past studies have variously attributed these changes to altered wave forcing from the tropics8, 10, 11, 12 or an altered zonal mean basic state in which the stationary wave activity propagates7, 13, 14, with a decisive explanation remaining elusive.

Here, we focus on the latest model projections of future eddy meridional wind (v), given its importance for regional hydroclimate5. Figure 1 presents an analysis of the Future–Past difference simulated by 35 Coupled Model Intercomparison Project, phase 5 (CMIP5) models (see Methods). The 300hPa response (Fig. 1b) is dominated by an approximately zonal wavenumber 5 pattern, reminiscent of the circumglobal teleconnection pattern prevalent in natural variability15. It is fairly barotropic (Fig. 1c) and, over North America, the low-level west coast southerlies and interior southwest northerlies contribute to wetting the US west coast and drying the interior southwest5. Such a response has been identified in a number of past studies8, 11, 12 and its structure is robust across the models, but there is a wide spread in magnitude (Fig. 1d). The implications of this spread for North American hydroclimate are seen in Fig. 1e, where the models are divided based on the strength of the 300hPa interior southwest v anomaly. The stronger half exhibits more west coast wetting and southern drying, as would be expected given the mean flow contributions to this precipitation–evaporation (P–E) change5. The relationship between v and P–E is presented in this format for use in the following analysis, but a similar assessment through correlation between southwest v and P–E exhibits similar features, with a correlation with west coast wetting of up to 0.77 and southwest drying of up to 0.56.

Figure 1: The DJF v response to climate change.
The DJF v[lowast] response to climate change.

a,b, Multi-model mean 300hPa v for Past (a, contour = 2m s−1) and Future–Past (b, contour  =  0.4ms−1). c, As for b at 700hPa. d, 300hPa v anomaly for each model in the seven boxed regions in b. These characterize the response over: the North American west coast (WC), interior southwest (SW) and east coast (EC), the Western and Eastern Mediterranean (WM and EM), the Persian Gulf (PG) and central Asia (AS). e, The P–E response for (top left) CMIP5 multi-model mean, (top right and bottom right) models in the weakest and strongest halves of the v distribution in the SW box, respectively, and (bottom left) the difference between the strong and weak responses (grey not statistically significant at the 95% level by a two-tailed t-test).

CMIP5 analysis.

35 models from the CMIP5 archive are analysed (Supplementary Table 1). The ‘Past is defined as 1979–2005 of the historical simulation and the ‘Future as 2070–2099 of the RCP8.5 scenario. Model ensemble averages are calculated first. The December, January, February (DJF) meridional wind (v), zonal wind (u), precipitation (P) and evaporation (E) are used in Figs 14 and 5. Comparison is made with the 1979–2005 ERA-Interim reanalysis climatology20.

Stationary wave modelling.

Figures 2 and 3 present results using an idealized stationary wave model. This model, described in detail in ref. 28, is a time-dependent baroclinic model that solves the nonlinear primitive equations for deviations from a prescribed zonal mean basic state in response to zonally asymmetric imposed forcings. We use 24 vertical sigma (σ) levels and and rhomboidal truncation at wavenumber 30 in the horizontal (R30). Rayleigh friction is applied to the zonal and meridional winds at the lowest four levels with timescales of 0.3, 0.5, 1 and 8 days (shortest at the surface). To prevent baroclinic instability, an interior Rayleigh drag is imposed with a 15-day timescale along with a strong biharmonic diffusion (coefficient of 1 × 1017) and a 15-day Newtonian relaxation of the temperature field towards the basic state (similar to ref. 6). The influence of damping timescales was tested between 10 and 30 days and results were found to be insensitive over this range. Time integration is performed for 80 days with a relaxation of the zonal mean back to the basic state on a 3-day timescale. A quasi-steady state is reached by day 30 and the average from days 30 to 80 is shown.

The stationary wave model inputs are those of the CMIP5 multi-model mean (Supplementary Fig. 1). The basic state consists of u, v, temperature (T) and surface pressure (ps), first linearly interpolated onto the model σ levels before taking the zonal- and multi-model mean. Diabatic heating is derived as a residual from the thermodynamic equation on pressure levels using monthly mean fields, and therefore includes the sub-monthly transient eddy sensible heat flux convergence. Leaving these thermal forcings combined is considered reasonable given the close linkage between the transient eddy sensible and latent heat fluxes and the tendency for the transients to act diffusively on temperature gradients induced by other diabatic sources6, 29. The transient vorticity and divergence flux convergences are obtained for a subset of 17 models using the 6-hourly hybrid level u and v after first interpolating onto 17 pressure levels (as ref. 9). As high temporal resolution vertical velocities are not available, the contribution from the vertical eddy fluxes is neglected.

The Future–Past difference (Fig. 2b) is obtained by first running a simulation with the Past basic state, diabatic heating, transient vorticity/divergence forcing and orography (Fig. 2a), followed by a simulation with the future basic state, diabatic heating, transient vorticity/divergence forcing and orography, and then differencing. The contribution from the anomalous basic state, diabatic heating or transient fluxes is assessed by Future simulations in which only the Future input of interest is used and all other inputs are kept at Past values.

In Fig. 3, to assess the relative importance of particular aspects of future temperature change to the basic state influence, a thermal wind balanced zonal mean basic state is constructed. Here, the Future basic state consists of the zonal mean Past u, v, T and ps plus the Future–Past difference in zonal mean T and the corresponding thermal wind balanced u anomaly. Poleward of 15N/S, this u anomaly is obtained by integration of the meridional temperature gradient upward from the multi-model mean near-surface wind anomaly using thermal wind balance. This is pieced together with the actual wind anomaly equatorward of 15N/S, as thermal wind balance is not a good approximation in the tropics. For Fig. 3b, Arctic amplification and lower tropospheric wind anomalies are removed by setting the near-surface zonal mean wind anomalies to zero and zonal mean T anomalies to 4K everywhere below 0.5. Polar lower stratospheric cooling is removed by setting zonal mean T anomalies poleward of 42° N and between σ = 0.07 and σ = 0.3 to zero.

Stationary wave theory.

Results are interpreted using linear barotropic Rossby wave theory. The assumption of linearity is reasonable as we obtain similar conclusions with linear stationary wave model simulations. The relevant waves are deep barotropic structures, and therefore will be influenced by the winds throughout their depth (which extends above 100hPa). Throughout this discussion we assume that the larger zonal wind changes at 100hPa are, therefore, having an influence on the wave structures throughout the depth of the troposphere, and we make use of the wind anomalies at this level for the regression in Fig. 5, as it is where the anomalies are largest.

  1. Held, I. M. & Soden, B. J. Robust responses of the hydrological cycle to global warming. J. Clim. 19, 56865699 (2006).
  2. Seager, R., Naik, N. & Vecchi, G. A. Thermodynamic and dynamic mechanisms for large-scale changes in the hydrological cycle in response to global warming. J. Clim. 23, 46514668 (2010).
  3. Neelin, J. D., Langenbrunner, B., Meyerson, J. E., Hall, A. & Berg, N. California winter precipitation change under global warming in the Coupled Model Intercomparison Project phase 5 ensemble. J. Clim. 26, 62386256 (2013).
  4. Seager, R. et al. Causes of increasing aridification of the Mediterranean region in response to rising greenhouse gases. J. Clim. 27, 46554676 (2014).
  5. Seager, R. et al. Dynamical and thermodynamical causes of large-scale changes in the hydrological cycle over North America in response to global warming. J. Clim. 27, 79217948 (2014).
  6. Held, I. M., Ting, M. & Wang, H. Northern winter stationary waves: Theory and modeling. J. Clim. 15, 21252144 (2002).
  7. Brandefelt, J. & Körnich, H. Northern Hemisphere stationary waves in future climate projections. J. Clim. 21, 63416353 (2008).
  8. Haarsma, R. J. & Selten, F. Anthropogenic changes in the Walker circulation and their impact on the extra-tropical planetary wave structure in the Northern Hemisphere. Clim. Dynam. 39, 17811799 (2012).
URL: http://www.nature.com/nclimate/journal/v6/n1/full/nclimate2783.html
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/4595
Appears in Collections:气候变化事实与影响
科学计划与规划
气候变化与战略

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Isla R. Simpson. Causes of change in Northern Hemisphere winter meridional winds and regional hydroclimate[J]. Nature Climate Change,2015-09-07,Volume:6:Pages:65;70 (2016).
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