In this work, a high-resolution triple-nested implementation of the National Centers for Environmental Prediction (NCEP) operational Hurricane Weather Research and Forecasting Model (HWRF) for the 2012 hurricane season is evaluated. Statistics of retrospective experiments for the 2010–11 hurricane seasons show that the new configuration demonstrates significant improvement compared to the 2011 operational HWRF in terms of storm track, intensity, size, dynamical constraints between mass and wind field, and initial vortex imbalance. Specifically, the 5-day track and intensify forecast errors are improved by about 19% and 7% for the North Atlantic basin, and by 9% and 30% for the eastern Pacific basin, respectively. Verifications of storm size in terms of wind radii at 34-, 50-, and 64-kt (17.5, 25.7, and 32.9 m s−1) thresholds at different quadrants show dramatic improvement with most of the overestimation of the storm size in previous operational HWRF versions removed at all forecast times. In addition, dynamical constraints between the storm intensity and the outermost radius in the new configuration are consistent with the best track data. The relationship between minimum sea level pressure and maximum 10-m wind is also improved in both basins, indicating that the storm dynamics and structure have been improved in the 2012 HWRF compared to the previous versions. These significant improvements obtained with the new HWRF implementation are attributed to a number of major changes including a new higher-resolution nest, improved vortex initialization, improved planetary boundary layer and turbulence physics, and some critical bug fixes related to the moving nest. Such improvements show that the new HWRF implementation is a promising upgrade for future hurricane seasons.

The next generation Hurricane Analysis and Forecast System (HAFS) has been developed recently in the National Oceanic and Atmospheric Administration (NOAA) to accelerate the improvement of tropical cyclone (TC) forecasts within the Unified Forecast System (UFS) framework. The finite-volume cubed sphere (FV3) based convection-allowing HAFS Stand-Alone Regional model (HAFS-SAR) was successfully implemented during Hurricane Forecast Improvement Project (HFIP) real-time experiments for the 2019 Atlantic TC season. HAFS-SAR has a single large 3-km horizontal resolution regional domain covering the North Atlantic basin. A total of 273 cases during the 2019 TC season are systematically evaluated against the best track and compared with three operational forecasting systems: Global Forecast System (GFS), Hurricane Weather Research and Forecasting model (HWRF), and Hurricanes in a Multi-scale Ocean-coupled Non-hydrostatic model (HMON). HAFS-SAR has the best performance in track forecasts among the models presented in this study. The intensity forecasts are improved over GFS, but show less skill compared to HWRF and HMON. The radius of gale force wind is over-predicted in HAFS-SAR, while the hurricane force wind radius has lower error than other models.

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.

The NEMS GFS Aerosol Component Version 2.0 (NGACv2) for global multispecies aerosol forecast has been developed at the National Centers of Environment Prediction (NCEP) in collaboration with the NESDIS Center for Satellite Applications and Research (STAR), the NASA Goddard Space Flight Center (GSFC), and the University at Albany, State University of New York (SUNYA). This paper describes the continuous development of the NGAC system at NCEP after the initial global dust-only forecast implementation (NGAC version 1.0, NGACv1). With NGACv2, additional sea salt, sulfate, organic carbon, and black carbon aerosol species were included. The smoke emissions are from the NESDIS STAR's Global Biomass Burning Product (GBBEPx), blended from the global biomass burning emission product from a constellation of geostationary satellites (GBBEP-Geo) and GSFC's Quick Fire Emission Data Version 2 from a polar-orbiting sensor (QFED2). This implementation advanced the global aerosol forecast capability and made a step forward toward developing a global aerosol data assimilation system. The aerosol products from this system have been used by many applications such as for regional air quality model lateral boundary conditions, satellite sea surface temperature (SST) physical retrievals, and the global solar insolation estimation. Positive impacts have been seen in these applications.

This study presents evaluation of real-time performance of the National Centers for Environmental Prediction (NCEP) operational Hurricane Weather Research and Forecast (HWRF) modeling system upgraded and implemented in 2013 in the western North Pacific basin (WPAC). Retrospective experiments with the 2013 version of the HWRF Model upgrades for 2012 WPAC tropical cyclones (TCs) show significant forecast improvement compared to the real-time forecasts from the 2012 version of HWRF. Despite a larger number of strong storms in the WPAC during 2013, real-time forecasts from the 2013 HWRF (H213) showed an overall reduction in intensity forecast errors, mostly at the 4–5-day lead times. Verification of the H213’s skill against the climate persistence forecasts shows that although part of such improvements in 2013 is related to the different seasonal characteristics between the years 2012 and 2013, the new model upgrades implemented in 2013 could provide some further improvement that the 2012 version of HWRF could not achieve. Further examination of rapid intensification (RI) events demonstrates noticeable skill of H213 with the probability of detection (POD) index of 0.22 in 2013 compared to 0.09 in 2012, suggesting that H213 starts to show skill in predicting RI events in the WPAC.

This study documents the recent efforts of the hurricane modeling team at the National Centers for Environmental Prediction’s (NCEP) Environmental Modeling Center (EMC) in implementing the operational Hurricane Weather Research and Forecasting Model (HWRF) for real-time tropical cyclone (TC) forecast guidance in the western North Pacific basin (WPAC) from May to December 2012 in support of the operational forecasters at the Joint Typhoon Warning Center (JTWC). Evaluation of model performance for the WPAC in 2012 reveals that the model has promising skill with the 3-, 4-, and 5-day track errors being 125, 220, and 290 nautical miles (n mi; 1 n mi = 1.852 km), respectively. Intensity forecasts also show good performance, with the most significant intensity error reduction achieved during the first 24 h. Stratification of the track and intensity forecast errors based on storm initial intensity reveals that HWRF tends to underestimate storm intensity for weak storms and overestimate storm intensity for strong storms. Further analysis of the horizontal distribution of track and intensity forecast errors over the WPAC suggests that HWRF possesses a systematic negative intensity bias, slower movement, and a rightward bias in the lower latitudes. At higher latitudes near the East China Sea, HWRF shows a positive intensity bias and faster storm movement. This appears to be related to underestimation of the dominant large-scale system associated with the western Pacific subtropical high, which renders weaker steering flows in this basin.