Response of the North Pacific Storm Track Activity in the Cold Season to Multi-scale Oceanic Variations of Kuroshio Extension System: A Statistical Assessment

In this paper,a statistical method called Generalized Equilibrium Feedback Analysis(GEFA)is used to investigate the responses of the North Pacific Storm Track(NPST)in the cold season to the multi-scale oceanic variations of the Kuroshio Extension(KE)system,including its large-scale variation,oceanic front meridional shift,and mesoscale eddy activity.Results show that in the cold season from the lower to the upper troposphere,the KE large-scale variation significantly weakens the storm track activity over the central North Pacific south of 30°N.The northward shift of the KE front significantly strengthens the storm track activity over the western and central North Pacific south of 40°N,resulting in a southward shift of the NPST.In contrast,the NPST response to KE mesoscale eddy activity is not so significant and relatively shallow,which only shows some significant positive signals near the dateline in the lower and middle troposphere.Furthermore,it is found that baroclinicity and baroclinic energy conversion play an important role in the formation of the NPST response to the KE multi-scale oceanic variations.

A comparison of the strength and position variability of the Kuroshio Extension SST front

This study compares the seasonal and interannual-to-decadal variability in the strength and position of the Kuroshio Extension front(KEF)using high-resolution satellite-derived sea surface temperature(SST)and sea surface height(SSH)data.Results show that the KEF strength has an obvious seasonal variation that is similar at different longitudes,with a stronger(weaker)KEF during the cold(warm)season.However,the seasonal variation in the KEF position is relatively weak and varies with longitude.In contrast,the low-frequency variation of the KEF position is more distinct than that of the KEF strength even though they are well correlated.On both seasonal and interannual-to-decadal time scales,the western part of the KEF(142°–144°E)has the greatest variability in strength,while the eastern part of the KEF(149°–155°E)has the greatest variability in position.In addition,the relationships between wind-forced Rossby waves and the low-frequency variability in the KEF strength and position are also discussed by using the statistical analysis methods and a wind-driven hindcast model.A positive(negative)North Pacific Oscillation(NPO)-like atmospheric forcing generates positive(negative)SSH anomalies over the central North Pacific.These oceanic signals then propagate westward as Rossby waves,reaching the KE region about three years later,favoring a strengthened(weakened)and northward(southward)-moving KEF.

Predictability of the 7·20 extreme rainstorm in Zhengzhou in stochastic kinetic-energy backscatter ensembles

The scale-dependent predictability of the devastating 7·20 extreme rainstorm in Zhengzhou,China in 2021 was investigated via ensemble experiments,which were perturbed on different scales using the stochastic kinetic-energy backscatter(SKEB)scheme in the WRF model,with the innermost domain having a 3-km grid spacing.The daily rainfall(RAIN24h)and the cloudburst during 1600-1700 LST(RAIN1h)were considered.Results demonstrated that with larger perturbation scales,the ensemble spread for the rainfall maximum widens and rainfall forecasts become closer to the observations.In ensembles with mesoscale or convective-scale perturbations,RAIN1h loses predictability at scales smaller than 20 km and RAIN24h is predictable for all scales.Whereas in ensembles with synoptic-scale perturbations,the largest scale of predictability loss extends to 60 km for both RAIN1h and RAIN24h.Moreover,the average positional error in forecasting the heaviest rainfall for RAIN24h(RAIN1h)was 400 km(50-60)km.The southerly low-level jet near Zhengzhou was assumed to be directly responsible for the forecast uncertainty of RAIN1h.The rapid intensification in low-level cyclonic vorticity,mid-level divergence,and upward motion concomitant with the jet dynamically facilitated the cloudburst.Further analysis of the divergent,rotational and vertical kinetic spectra and the corresponding error spectra showed that the error kinetic energy at smaller scales grows faster than that at larger scales and saturates more quickly in all experiments.Larger-scale perturbations not only boost larger-scale error growth but are also conducive to error growth at all scales through a downscale cascade,which indicates that improving the accuracy of larger-scale flow forecast may discernibly contributes to the forecast of cloudburst intensity and position.