The Spatial Patterns of Initial Errors Related to the “Winter Predictability Barrier” of the Indian Ocean Dipole

In this study, using the Geophysical Fluid Dynamics Laboratory Climate Model version 2pl （GFDL CM2pl） coupled model, the winter predictability barrier （WPB） is found to exist in the model not only in the growing phase but also the Indian Ocean dipole （IOD） decaying phase of positive events due to the effect of initial errors. In particular, the WPB is stronger in the growing phase than in the decaying phase. These results indicate that initial errors can cause the WPB. The domi- nant patterns of the initial errors that cause the occurrence of the WPB often present an eastern-western dipole both in the surface and subsurface temperature components. These initial errors tend to concentrate in a few areas, and these areas may represent the sensitive areas of the predictions of positive IOD events. By increasing observations over these areas and eliminating initial errors here, the WPB phenomenon may be largely weakened and the forecast skill greatly improved.

The“Spring Predictability Barrier” Phenomenon of ENSO Predictions Generated with the FGOALS-g Model

Using the sea surface temperature （SST） predicted for the equatorial Pacific Ocean by the Flexible Global Ocean-Atmosphere-Land System Model-gamil （FGOALS-g）, an analysis of the prediction errors was performed for the seasonally dependent predictability of SST anomalies both for neutral years and for the growth/decay phase of El Nino/La Nina events. The study results indicated that for the SST predictions relating to the growth phase and the decay phase of El Nino events, the prediction errors have a seasonally dependent evolution. The largest increase in errors occurred in the spring season, which indicates that a prominent spring predictability barrier （SPB） occurs during an El Nino-Southern Oscillation （ENSO） warming episode. Furthermore, the SPB associated with the growth-phase prediction is more prominent than that associated with the decay-phase prediction. However, for the neutral years and for the growth and decay phases of La Nifia events, the SPB phenomenon was less prominent. These results indicate that the SPB phenomenon depends extensively on the ENSO events themselves. In particular, the SPB depends on the phases of the ENSO events. These results may provide useful knowledge for improving ENSO forecasting.

Interannual Relationship between the Winter Aleutian Low and Rainfall in the Following Summer in South China

Using observations and reanalysis data, this study investigates the interannual relationship between the winter Aleutian Low(AL) and the rainfall anomalies in the following summer in South China(SC). Results show that the winter AL is significantly positively(negatively) correlated with the SC rainfall anomalies in the following July(August). Specifically, SC rainfall anomalies have a tendency to be positive(negative) in July(August) when the preceding winter AL is stronger than normal. The winter AL-related atmospheric circulation anomalies in the following summer are also examined. When the winter AL is stronger, there is a significant anticyclonic(cyclonic) circulation anomaly over the subtropical western North Pacific in the following July(August). Southerly(northerly) wind anomalies to the west of this anomalous anticyclonic(cyclonic) circulation increase(decrease) the northward moisture transportation and contribute to the positive(negative) rainfall anomalies over SC in July(August). This study indicates that the AL in the preceding winter can be used as a potential predictor of the rainfall anomalies in the following July and August over SC.

Ensemble Forecast for Tropical Cyclone Based on CNOP-P Method:A Case Study of WRF Model and Two Typhoons

In this paper,we set out to study the ensemble forecast for tropical cyclones.The case study is based on the Conditional Nonlinear Optimal Perturbation related to Parameter(CNOP-P)method and the WRF model to improve the prediction accuracy for track and intensity,and two different typhoons are selected as cases for analysis.We first select perturbed parameters in the YSU and WSM6 schemes,and then solve CNOP-Ps with simulated annealing algorithm for single parameters as well as the combination of multiple parameters.Finally,perturbations are imposed on default parameter values to generate the ensemble members.The whole proposed procedures are referred to as the PerturbedParameter Ensemble(PPE).We also conduct two experiments,which are control forecast and ensemble forecast,termed Ctrl and perturbed-physics ensemble(PPhyE)respectively,to demonstrate the performance for contrast.In the article,we compare the effects of three experiments on tropical cyclones in aspects of track and intensity,respectively.For track,the prediction errors of PPE are smaller.The ensemble mean of PPE filters the unpredictable situation and retains the reasonably predictable components of the ensemble members.As for intensity,ensemble mean values of the central minimum sea-level pressure and the central maximum wind speed are closer to CMA data during most of the simulation time.The predicted values of the PPE ensemble members included the intensity of CMA data when the typhoon made landfall.The PPE also shows uncertainty in the forecast.Moreover,we also analyze the track and intensity from physical variable fields of PPE.Experiment results show PPE outperforms the other two benchmarks in track and intensity prediction.

Time-Dependent Nonlinear Forcing Singular Vector-Type Tendency Error of the Zebiak-Cane Model

Based on the Zebiak-Cane model, the timedependent nonlinear forcing singular vector （NFSV）-type tendency errors with components of 4 and 12 （denoted by NFSV-4 and NFSV-12） are calculated for predetermined El Nifio events and compared with the constant NFSV （denoted by NFSV-1） from their patterns and resultant prediction errors. Specifically, NFSV-1 has a zonal dipolar sea surface temperature anomaly （SSTA） pattern with negative anomalies in the equatorial eastern Pacific and positive anomalies in the equatorial central-western Pa- cific. Although the first few components in NFSV-4 and NFSV-12 present patterns similar to NFSV-1, they tend to extend their dipoles farther westward; meanwhile, the positive anomalies gradually cover much smaller regions with the lag times. In addition, the authors calculate the predic- tion errors caused by the three kinds of NFSVs, and the results indicate that the prediction error induced by NFSV-12 is the largest, followed by the NFSV-4. However, when compared with the prediction errors caused by random tendency errors, the NFSVs generate significantly larger prediction errors. It is therefore shown that the spatial structure of tendency errors is important for producing large prediction errors. Furthermore, in exploring the tendency errors that cause the largest prediction error for E1 Nifio events, the timedependent NFSV should be evaluated.

The Combined Effect of Initial Error and Model Error on ENSO Prediction Uncertainty Generated by the Zebiak-Cane Model

Initial errors and model errors are the source of prediction errors. In this study, the authors compute the conditional nonlinear optimal perturbation （CNOP）-type initial errors and nonlinear forcing singular vector （NFSV）- type tendency errors of the Zebiak-Cane model with respect to El Nifio events and analyze their combined effect on the prediction errors for E1 Nino events. The CNOP- type initial error （NFSV-type tendency error） represents the initial errors （model errors） that have the largest effect on prediction uncertainties for E1 Nifio events under the perfect model （perfect initial conditions） scenario. How- ever, when the CNOP-type initial errors and the NFSV- type tendency errors are simultaneously considered in the model, the prediction errors caused by them are not am- plified as the authors expected. Specifically, the predic- tion errors caused by the combined mode of CNOP-type initial errors and NFSV-type tendency errors are a little larger than those caused by the NFSV-type tendency er- rors. This fact emphasizes a need to investigate the opti- mal combined mode of initial errors and tendency errors that cause the largest prediction error for E1 Nifio events.

The Amplitude-Duration Relation of Observed El Nio Events

The authors demonstrate that the E1 Nifio events in the pre- and post-1976 periods show two ampli- tude-duration relations. One is that the stronger E1 Nifio events have longer durations, which is robust for the moderate E1 Nifio events; the other is that the stronger E1 Nifio events have shorter durations but for strong E1 Nifio events. By estimating the sign and amplitude of the nonlinear dynamical heating （NDH） anomalies, the au- thors illustrate that the NDH anomalies are negligible for moderate E1 Nifio events but large for strong E1 Nifio events. In particular, the large NDH anomalies for strong E1 Nifio events are positive during the growth and mature phases, which favor warmer E1 Nifio events. During the decay phase, however, the negative NDH anomalies start to arise and become increasingly significant with the evolution of the E1 Nifio events, in which the negative NDH anomalies dampen the sea surface temperature anomalies （SSTA） and cause the E1 Nifio events to reach the SST normal state earlier. This pattern suggests that the nonlinearity tends to increase the intensities of strong E1 Nifio events and shorten their duration, which, together with the previous results showing a positive correlation between the strength of E1 Nifio events and the signifi- cance of the effect of nonlinear advection on the events （especially the suppression of nonlinearity on the SSTA during the decay phase）, shows that the strong E1 Nifio events tend to have the amplitude-duration relation of the stronger E1 Nifio events with shorter durations. This result also lends support to the assertion that moderate E1 Nifio events possess the amplitude-duration relation of stronger E1 Nifio events with longer durations.