Xiaqiong Zhou

Mechanism of Concentric Eyewall Replacement Cycles and Associated Intensity Change

AbstractTo understand the mechanisms responsible for the secondary eyewall replacement cycles and associated intensity changes in intense tropical cyclones (TCs), two numerical experiments are conducted in this study with the Weather Research and Forecasting (WRF) model. In the experiments, identical initial conditions and model parameters are utilized except that the concentration of ice particles is enhanced in the sensitivity run. With enhanced ice concentrations, it is found that the secondary eyewall forms at an increased radius, the time required for eyewall replacement is extended, and the intensity fluctuation is relatively large. The enhanced concentrations of ice particles at the upper tropospheric outflow layer produces a noticeable subsidence region (moat) surrounding the primary eyewall. The presence of the moat forces the secondary eyewall to form at a relatively large radius. The axisymmetric equivalent potential temperature budget analysis reveals that the demise of the inner eyewall is pr...

Impact of Secondary Eyewall Heating on Tropical Cyclone Intensity Change

Abstract The primary goal of this study is to explore the factors that might influence the intensity change of tropical cyclones (TCs) associated with secondary eyewall replacement. Concentric eyewall structures in TCs with and without large intensity weakening are compared using the Tropical Rainfall Measuring Mission (TRMM) 2A12 and 2A25 data. It is found that the secondary eyewalls with a stratiform-type heating profile show a marked weakening, while those TCs with a convective-type heating weaken insignificantly or even intensify. This observed feature is supported by a set of sensitivity numerical experiments performed with the Weather Research and Forecasting model. With more active convection, the latent heat released in the outer eyewall and moat region can better sustain storm intensity. The prevailing stratiform precipitation results in low equivalent potential temperature air in the moat and reduces the entropy of the boundary layer inflow to the inner eyewall through persistent downdrafts, lea...

Performance of the New NCEP Global Ensemble Forecast System in a Parallel Experiment

AbstractA new version of the Global Ensemble Forecast System (GEFS, v11) is tested and compared with the operational version (v10) in a 2-yr parallel run. The breeding-based scheme with ensemble transformation and rescaling (ETR) used in the operational GEFS is replaced by the ensemble Kalman filter (EnKF) to generate initial ensemble perturbations. The global medium-range forecast model and the Global Forecast System (GFS) analysis used as the initial conditions are upgraded to the GFS 2015 implementation version. The horizontal resolution of GEFS increases from Eulerian T254 (~52 km) for the first 8 days of the forecast and T190 (~70 km) for the second 8 days to semi-Lagrangian T574 (~34 km) and T382 (~52 km), respectively. The sigma pressure hybrid vertical layers increase from 42 to 64 levels. The verification of geopotential height, temperature, and wind fields at selected levels shows that the new GEFS significantly outperforms the operational GEFS up to days 8–10 except for an increased warm bias o...

Ensemble Transform with 3D Rescaling Initialization Method

AbstractThe ensemble transform with rescaling (ETR) method has been used to produce fast-growing components of analysis error in the NCEP Global Ensemble Forecast System (GEFS). The rescaling mask contained in the ETR method constrains the amplitude of perturbations to reflect regional variations of analysis error. However, because of a lack of suitable three-dimensional (3D) analysis error estimation, in the operational GEFS the mask is based on the estimated analysis error at 500 hPa and is not flow dependent but changes monthly. With the availability of an ensemble-based data assimilation system at NCEP, a 3D mask can be computed. This study generates initial perturbations by the ensemble transform with 3D rescaling (ET_3DR) and compares the performance with the ETR. Meanwhile, the ET_3DR is also applied within the ensemble Kalman filter (EnKF) method (hereafter EnKF_3DR).Results from a set of experiments indicate that the 3D mask suppresses perturbations less in unstable regions. Relative to the ETR, ...

Impact of Sea Surface Temperature Forcing on Weeks 3 and 4 Forecast Skill in the NCEP Global Ensemble Forecasting System

AbstractThe Global Ensemble Forecasting System (GEFS) is being extended from 16 to 35 days to cover the subseasonal period, bridging weather and seasonal forecasts. In this study, the impact of SST forcing on the extended-range land-only global 2-m temperature, continental United States (CONUS) accumulated precipitation, and MJO skill are explored with version 11 of the GEFS (GEFSv11) under various SST forcing configurations. The configurations consist of 1) the operational GEFS 90-day e-folding time of the observed real-time global SST (RTG-SST) anomaly relaxed to climatology, 2) an optimal AMIP configuration using the observed daily RTG-SST analysis, 3) a two-tier approach using the CFSv2-predicted daily SST, and 4) a two-tier approach using bias-corrected CFSv2-predicted SST, updated every 24 h. The experimental period covers the fall of 2013 and the winter of 2013/14. The results indicate that there are small differences in the ranked probability skill scores (RPSSs) between the various SST forcing ex...

Toward the Improvement of Subseasonal Prediction in the National Centers for Environmental Prediction Global Ensemble Forecast System

In order to provide ensemble-based subseasonal (weeks 3 and 4) forecasts to support the operational mission of the Climate Prediction Center, National Centers for Environmental Prediction, experiments have been designed through the Subseasonal Experiment (SubX) project to investigate the predictability in both tropical and extratropical regions. The control experiment simply extends the current operational Global Ensemble Forecast System (GEFS; version 11) from 16 to 35 days. In addition to the control, the parallel experiments will be mainly designed to focus on three areas: (1) improving model uncertainty representation for the tropics through stochastic physical perturbations; (2) considering the impact of the ocean by using a two-tiered sea surface temperature approach; and (3) testing a new scale-aware convection scheme to improve the model physics for tropical convection and Madden-Julian Oscillation (MJO) forecasts. All experiments are initialized every 5 days at 0000 UTC during the period of May 2014–May 2016 (25 months). In the tropics, MJO forecast skill has been improved from an average of 12.5 days (control) to nearly 22 days by combining all three modifications to GEFS. In the extratropics, the ensemble mean anomaly correlation of 500-hPa geopotential height improved over weeks 3 and 4. In addition, the Continuous Ranked Probability Score (of the Northern Hemisphere raw surface temperature (land only) is improved as well. A similar result is found in the Contiguous United States precipitation, although forecast skill is extremely low. Our results imply that calibration may be important and necessary for surface temperature and precipitation forecast for the subseasonal timescale due to the large systematic model errors.