An enhanced version of the hybrid ensemble-three-dimensional variational data assimilation (3DVAR) system for the Weather Research and Forecasting Model (WRF) is applied to the assimilation of radial velocity (Vr) data from two coastal Weather Surveillance Radar-1988 Doppler (WSR-88D) radars for the prediction of Hurricane Ike (2008) before and during its landfall. In this hybrid system, flow-dependent ensemble covariance is incorporated into the variational cost function using the extended control variable method. The analysis ensemble is generated by updating each forecast ensemble member with perturbed radar observations using the hybrid scheme itself. The Vr data are assimilated every 30 min for 3 h immediately after Ike entered the coverage of the two coastal radars.The hybrid method produces positive temperature increments indicating a warming of the inner core throughout the depth of the hurricane. In contrast, the 3DVAR produces much weaker and smoother increments with negative values at the vortex center at lower levels. Wind forecasts from the hybrid analyses fit the observed radial velocity better than that from 3DVAR, and the 3-h accumulated precipitation forecasts from the hybrid are also more skillful. The track forecast is slightly improved by the hybrid method and slightly degraded by the 3DVAR compared to the forecast from the Global Forecast System (GFS) analysis. All experiments assimilating the radar data show much improved intensity analyses and forecasts compared to the experiment without assimilating radar data. The better forecast of the hybrid indicates that the hybrid method produces dynamically more consistent state estimations. Little benefit of including the tuned static component of background error covariance in the hybrid is found.
The hybrid Ensemble Kalman Filter -Variational (EnKF-Var) data assimilation (DA) system based on Grid-point Statistical Interpolation (GSI) is extended for the Hurricane-WRF model (HWRF). Background ensemble forecasts initialized by the EnKF are used to provide the flow-dependent error covariance to be ingested by GSI using the extended control variable method. The hybrid system is then applied to assimilate airborne radar data.In this article, the newly developed HWRF hybrid system capable of assimilating airborne radar observations is introduced. The impact of using variously estimated background error covariances on tropical cyclone (TC) core analyses and subsequent forecasts is explored by a detailed study of Hurricane Sandy (2012) and by systematic comparison of various sensitivity experiments for multiple cases during the 2012-2013 seasons. The hybrid system using the HWRF EnKF ensemble covariance (Hybrid-HENS) is able to correct both the wind and mass fields in a dynamically and thermodynamically coherent fashion. In contrast, the wind and pressure adjustments by GSI three-dimensional variation (GSI3DVar) using the static covariance are inconsistent. The wind and pressure relation in the covariances derived from the GFS ensemble (Hybrid-GENS) improves upon the static covariance, but is still inconsistent compared to that of HWRF. Verifications against independent flight-level and Stepped Frequency Microwave Radiometer (SFMR) wind data, and Hurricane Research Division (HRD) radar wind composite reveal that the Hybrid-HENS system improves the analysed TC structure upon both GSI3DVar and Hybrid-GENS. Hybrid-HENS and Hybrid-GENS improve the track, minimum sea-level pressure (MSLP) and Vmax forecast relative to GSI3DVar. Hybrid-HENS further improves track forecasts compared to Hybrid-GENS. Hybrid-HENS provides the largest positive impact of the airborne radar data. In comparison, GSI3DVar shows consistently negative impact of the data when analysing the structure and verifying track forecasts. Blending the static background error covariance in the hybrid system improves the maximum wind forecast while little benefit is found in the analysed structures and the MSLP and track forecasts.
Post-treatment is crucial to improve the comprehensive performance of laser-cladded martensitic stainless steel coatings. In this work, a low-temperature tempering treatment (210 °C), for the first time, was performed on the laser-cladded AISI 420 martensitic stainless steel coating. The microstructure and properties of the pre- and post-tempering specimens were carefully investigated by XRD, SEM, TEM, a micro-hardness tester, a universal material testing machine and an electrochemical workstation. The results show that the as-cladded AISI 420 stainless steel coating mainly consisted of martensite, austenite, Fe3C and M23C6 carbides. The phase constituent of the coating remained the same, however, the martensite decomposed into finer tempered martensite with the precipitation of numerous nano-sized Fe3C carbides and reverted austenite in the as-tempered specimen. Moreover, a slight reduction was found in the micro-hardness and tensile strength, while a significant increase in elongation was achieved after tempering. The fractography showed a transition from brittle fracture to ductile fracture accordingly. The as-tempered coating exhibited a striking combination of mechanical properties and corrosion resistance. This work can provide a potential strategy to enhance the overall properties of the laser-deposited Fe-based coating for industrial applications.
A detailed observational and Weather Research and Forecasting (WRF) model analysis utilizing Weather Surveillance Radar-1988 Doppler (WSR-88D), surface, and upper-air observations, as well as Geostationary Operational Environmental Satellite (GOES) images, shows a chain of events that leads to the formation of two prefrontal squall lines along the western Gulf coast on 29-30 April 2005. An approaching surface cold front (CF) generated an atmospheric bore that propagated along an inversion layer and excited highfrequency, low-level tropospheric gravity waves, initiating a squall line 60 km east of the cold front. This sequence of events manifested itself as low-level convergence ahead of the CF, which was detected by nearby WSR-88D radars. Two WRF model experiments were conducted in which one assimilated conventional observations (CTRL), and another included radar radial winds from nine WSR-88D locations (denoted as RADAR). Better representation of the low-level kinematics in RADAR yielded a distinct convergence line associated with the primary squall line.The RADAR experiment, as well as observations (such as an 0600 UTC Slidell, Louisiana, sounding), show that the secondary squall line formed ahead of the primary squall line due to high water vapor and warm temperature advection from the Gulf of Mexico that, when combined with a deep dry layer above the atmospheric boundary layer (ABL), destabilized the atmosphere. Concurrently, a lower-tropospheric trough, propagating faster than the surface front, enhanced lifting in the region and instigated the formation of new convection. RADAR forecasted the secondary convection not only in the right place but also at about the right time, while the CTRL experiment completely missed this secondary convection.
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