Seasonality of the Lagged Relationship between ENSO and the Northern Hemispheric Polar Vortex Variability

<Abstract>This paper reports the seasonal feature of the relationship between ENSO and the stratospheric Polar Vortex Oscillation (PVO) variability in the Northern Hemisphere.It is shown that the lagged ENSO-PVO coupling relationship exhibits distinct seasonal feature,due to the strong seasonality of PVO and ENSO.Specifically,the PVO variability not only during winter,but also in autumn and spring months,is significantly correlated with ENSO anomalies leading by seasons;however,no significant effect of ENSO is found on the PVO variability in winter months of November and February.Although a significant ENSO effect is primarily observed when ENSO leads PVO by about one year,a significant correlation is also found between PVO in the following spring months (M +1 A +1) and ENSO anomalies in the previous autumn (A-1 S-1 O- 1 N -1) when ENSO anomalies lead by about 18 months.The significant correlation between PVO in various seasons and the corresponding ENSO anomalies leading by seasons could be explicitly verified in most of the individual years,confirming that the lagged ENSO effect can largely modulate the seasonal timescale variability of PVO.Moreover,the composite spatial patterns of the zonal-mean temperature anomalies further show that the ENSO effect on the PVO in various seasons is related to the interannual variability of the seasonal timescale PVO events.

Statistical Characteristics of ENSO Events in CMIP5 Models

By applying the historical-run outputs from 24 Coupled Model Intercomparison Project Phase 5(CMIP5) models and the NOAA Extended Reconstructed SST V3 b dataset(ERSST), the characteristics of different types of ENSO in the selected CMIP5 models, including cold-season-matured Eastern Pacific(C-EP) ENSO, warmseason-matured EP(W-EP) ENSO, cold-season-matured Central Pacific(C-CP) ENSO, and warm-season-matured CP(W-CP) ENSO, were examined in comparison with those in the ERSST dataset. The results showed that, in general, consistent with observations, EP ENSO events in most of the model runs were relatively much stronger than CP ENSO events, and cold-season-matured ENSO events were relatively much more frequent than warm-season-matured ENSO events for both EP and CP ENSO events. The composite amplitudes of ENSO events in most of the models were generally weaker than in observations, particularly for EP El Ni?o and CP La Ni?a. Moreover, most of the models successfully reproduced the amplitude asymmetries between El Ni?o and La Ni?a for cold-season-matured EP and CP ENSO events, exhibiting an average stronger/weaker EP El Ni?o/La Ni?a regime and a weaker/stronger CP El Ni?o/La Ni?a regime. Most of the models, however, failed to reproduce the observed regimes of stronger/weaker W-EP El Ni?o/ La Ni?a and weaker/stronger W-CP El Ni?o/La Ni?a.

Understanding the Global Surface-Atmosphere Energy Balance in FGOALS-s2 through an Attribution Analysis of the Global Temperature Biases

Based on an attribution analysis of the global mean temperature biases in the Flexible Global OceanAtmosphere-Land System model, spectral version 2(FGOALS-s2) through a coupled atmosphere-surface climate feedback-response analysis method(CFRAM), the model's global surface-atmosphere energy balance in boreal winter and summer is examined. Within the energy-balance-based CFRAM system, the model temperature biases are attributed to energy perturbations resulting from model biases in individual radiative and non-radiative processes in the atmosphere and at the surface. The results show that, although the global mean surface temperature(Ts) bias is only 0.38 K in January and 1.70 K in July, and the atmospheric temperature(Ta) biases from the troposphere to the stratosphere are only around ±3 K at most, the temperature biases due to model biases in representing the individual radiative and non-radiative processes are considerably large(over ±10 K at most). Specifically, the global cold radiative Ts bias, mainly due to the overestimated surface albedo, is compensated for by the global warm non-radiative Ts bias that is mainly due to the overestimated downward surface heat fluxes. The model biases in non-radiative processes in the lower troposphere(up to 5–15 K) are relatively much larger than in upper levels, which are mainly responsible for the warm Ta biases there. In contrast, the global mean cold Ta biases in the mid-to-upper troposphere are mainly dominated by radiative processes. The warm/cold Ta biases in the lower/upper stratosphere are dominated by non-radiative processes, while the warm Ta biases in the mid-stratosphere can be attributed to the radiative ozone feedback process.