Impact of Resolution and Design on the U.S. Navy Global Ensemble Performance in the Tropics

2011 ◽  
Vol 139 (7) ◽  
pp. 2145-2155 ◽  
Author(s):  
Carolyn A. Reynolds ◽  
Justin G. McLay ◽  
James S. Goerss ◽  
Efren A. Serra ◽  
Daniel Hodyss ◽  
...  

Abstract The performance of the U.S. Navy global atmospheric ensemble prediction system is examined with a focus on tropical winds and tropical cyclone tracks. Ensembles are run at a triangular truncation of T119, T159, and T239, with 33, 17, and 9 ensemble members, respectively, to evaluate the impact of resolution versus the number of ensemble member tradeoffs on ensemble performance. Results indicate that the T159 and T239 ensemble mean tropical cyclone track errors are significantly smaller than those of the T119 ensemble out to 4 days. For ensemble forecasts of upper- and lower-tropospheric tropical winds, increasing resolution has only a small impact on ensemble mean root-mean-square error for wind speed, but does improve Brier scores for 10-m wind speed at the 5 m s−1 threshold. In addition to the resolution tests, modifications to the ensemble transform initial perturbation methodology and inclusion of stochastic kinetic energy backscatter are also evaluated. Stochastic kinetic energy backscatter substantially increases the ensemble spread and improves Brier scores in the tropics, but for the most part does not significantly reduce ensemble mean tropical cyclone track error.

2020 ◽  
Vol 148 (2) ◽  
pp. 825-847 ◽  
Author(s):  
Junkyung Kay ◽  
Xuguang Wang

Abstract A multiresolution ensemble (MR-ENS) method is developed to resolve a wider range of scales of the background error covariance (BEC) in the hybrid four-dimensional ensemble–variational (4DEnVar) while saving computational costs. MR-ENS is implemented in the NCEP Global Forecast System (GFS) gridpoint statistical interpolation (GSI) hybrid 4DEnVar. MR-ENS generates analysis increment by incorporating high-resolution static BEC and flow-dependent ensemble BECs from both high and low resolutions. MR-ENS is compared with three 4DEnVar update approaches: 1) the single-resolution (SR)-Low approach where the analysis increments are generated from the ensemble BEC and the static BEC at the same low resolution; 2) the dual-resolution (DR) approach where the analysis increment is generated using the high-resolution static BEC and low-resolution ensemble BEC; and 3) the SR-High approach, which is the same as 1) except that all covariances are at high-resolution. Experiments show that MR-ENS improves global and tropical cyclone track forecasts compared to SR-Low and DR. Inclusion of the high-resolution ensemble leads to increased background ensemble spread, better fitting of the background to observations, increased effective ranks, more accurate ensemble error correlation, and increased power of analysis increment at small scales. The majority of the improvement of MR-ENS relative to SR-Low is due to the partial use of high-resolution background ensemble. Compared to SR-High, MR-ENS decreases the overall cost by about 40% and shows comparable global and tropical cyclone track forecast performances. Diagnostics show that particularly in the tropics, MR-ENS improves the analysis increment over a wide range of scales and increases the effective rank of the ensemble BEC to the degree comparable to SR-High.


2016 ◽  
Vol 31 (1) ◽  
pp. 57-70 ◽  
Author(s):  
Lin Dong ◽  
Fuqing Zhang

Abstract An observation-based ensemble subsetting technique (OBEST) is developed for tropical cyclone track prediction in which a subset of members from either a single- or multimodel ensemble is selected based on the distance from the latest best-track position. The performance of OBEST is examined using both the 2-yr hindcasts for 2010–11 and the 2-yr operational predictions during 2012–13. It is found that OBEST outperforms both the simple ensemble mean (without subsetting) and the corresponding deterministic high-resolution control forecast for most forecast lead times up to 5 days. Applying OBEST to a superensemble of global ensembles from both the European Centre for Medium-Range Weather Forecasts and the National Centers for Environmental Prediction yielded a further reduction in track forecast errors by 5%–10% for lead times of 24–120 h.


1999 ◽  
Author(s):  
Scott R. Fulton ◽  
Nicole M. Burgess ◽  
Brittany L. Mitchell

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