scholarly journals Effect of background error tuning on assimilating radar radial velocity observations for the forecast of hurricane tracks and intensities

2019 ◽  
Vol 27 (1) ◽  
Author(s):  
Dongmei Xu ◽  
Feifei Shen ◽  
Jinzhong Min
2008 ◽  
Vol 136 (3) ◽  
pp. 945-963 ◽  
Author(s):  
Jidong Gao ◽  
Ming Xue

Abstract A new efficient dual-resolution (DR) data assimilation algorithm is developed based on the ensemble Kalman filter (EnKF) method and tested using simulated radar radial velocity data for a supercell storm. Radar observations are assimilated on both high-resolution and lower-resolution grids using the EnKF algorithm with flow-dependent background error covariances estimated from the lower-resolution ensemble. It is shown that the flow-dependent and dynamically evolved background error covariances thus estimated are effective in producing quality analyses on the high-resolution grid. The DR method has the advantage of being able to significantly reduce the computational cost of the EnKF analysis. In the system, the lower-resolution ensemble provides the flow-dependent background error covariance, while the single-high-resolution forecast and analysis provides the benefit of higher resolution, which is important for resolving the internal structures of thunderstorms. The relative smoothness of the covariance obtained from the lower 4-km-resolution ensemble does not appear to significantly degrade the quality of analysis. This is because the cross covariance among different variables is of first-order importance for “retrieving” unobserved variables from the radar radial velocity data. For the DR analysis, an ensemble size of 40 appears to be a reasonable choice with the use of a 4-km horizontal resolution in the ensemble and a 1-km resolution in the high-resolution analysis. Several sensitivity tests show that the DR EnKF system is quite robust to different observation errors. A 4-km thinned data resolution is a compromise that is acceptable under the constraint of real-time applications. A data density of 8 km leads to a significant degradation in the analysis.


2021 ◽  
Vol 149 (1) ◽  
pp. 21-40
Author(s):  
Rong Kong ◽  
Ming Xue ◽  
Chengsi Liu ◽  
Youngsun Jung

AbstractIn this study, a hybrid En3DVar data assimilation (DA) scheme is compared with 3DVar, EnKF, and pure En3DVar for the assimilation of radar data in a real tornadic storm case. Results using hydrometeor mixing ratios (CVq) or logarithmic mixing ratios (CVlogq) as the control variables are compared in the variational DA framework. To address the lack of radial velocity impact issues when using CVq, a procedure that assimilates reflectivity and radial velocity data in two separate analysis passes is adopted. Comparisons are made in terms of the root-mean-square innovations (RMSIs) as well as the intensity and structure of the analyzed and forecast storms. For pure En3DVar that uses 100% ensemble covariance, CVlogq and CVq have similar RMSIs in the velocity analyses, but errors grow faster during forecasts when using CVlogq. Introducing static background error covariance at 5% in hybrid En3DVar (with CVlogq) significantly reduces the forecast error growth. Pure En3DVar produces more intense reflectivity analyses than EnKF that more closely match the observations. Hybrid En3DVar with 50% outperforms other weights in terms of the RMSIs and forecasts of updraft helicity and is thus used in the final comparison with 3DVar and EnKF. The hybrid En3DVar is found to outperform EnKF in better capturing the intensity and structure of the analyzed and forecast storms and outperform 3DVAR in better capturing the intensity and evolution of the rotating updraft.


2012 ◽  
Vol 140 (11) ◽  
pp. 3507-3524 ◽  
Author(s):  
Yongzuo Li ◽  
Xuguang Wang ◽  
Ming Xue

Abstract 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.


Author(s):  
Ying Wang ◽  
Zhaoxia Pu

AbstractThe benefits of assimilating NEXRAD (Next Generation Weather Radar) radial velocity data for convective systems have been demonstrated in previous studies. However, impacts of assimilation of such high spatial and temporal resolution observations on hurricane forecasts has not been demonstrated with the NCEP (National Centers for Environmental Prediction) HWRF (Hurricane Weather and Research Forecasting) system. This study investigates impacts of NEXRAD radial velocity data on forecasts of the evolution of landfalling hurricanes with different configurations of data assimilation. The sensitivity of data assimilation results to influencing parameters within the data assimilation system, such as the maximum range of the radar data, super-observations, horizontal and vertical localization correlation length scale, and weight of background error covariances, is examined. Two hurricane cases, Florence and Michael, that occurred in the summer of 2018 are chosen to conduct a series of experiments. Results show that hurricane intensity, asymmetric structure of inland wind and precipitation, and quantitative precipitation forecasting are improved. Suggestions for implementation of operational configurations are provided.


1965 ◽  
Vol 5 ◽  
pp. 109-111
Author(s):  
Frederick R. West

There are certain visual double stars which, when close to a node of their relative orbit, should have enough radial velocity difference (10-20 km/s) that the spectra of the two component stars will appear resolved on high-dispersion spectrograms (5 Å/mm or less) obtainable by use of modern coudé and solar spectrographs on bright stars. Both star images are then recorded simultaneously on the spectrograph slit, so that two stellar components will appear on each spectrogram.


1976 ◽  
Vol 32 ◽  
pp. 613-622
Author(s):  
I.A. Aslanov ◽  
Yu.S. Rustamov

SummaryMeasurements of the radial velocities and magnetic field strength of β CrB were carried out. It is shown that there is a variability with the rotation period different for various elements. The curve of the magnetic field variation measured from lines of 5 different elements: FeI, CrI, CrII, TiII, ScII and CaI has a complex shape specific for each element. This may be due to the presence of magnetic spots on the stellar surface. A comparison with the radial velocity curves suggests the presence of a least 4 spots of Ti and Cr coinciding with magnetic spots. A change of the magnetic field with optical depth is shown. The curve of the Heffvariation with the rotation period is given. A possibility of secular variations of the magnetic field is shown.


2015 ◽  
Vol 71-72 ◽  
pp. 127-128
Author(s):  
B.J. Hrivnak ◽  
W. Lu ◽  
G. Van de Steene ◽  
H. Van Winckel ◽  
J. Sperauskas ◽  
...  

GPS Solutions ◽  
2021 ◽  
Vol 25 (2) ◽  
Author(s):  
Yohannes Getachew Ejigu ◽  
Felix Norman Teferle ◽  
Anna Klos ◽  
Bogusz Janusz ◽  
Addisu Hunegnaw

AbstractWe have reconstructed integrated water vapor (IWV) using the zenith wet delays to track the properties of hurricanes and explore their spatial and temporal distributions estimated from 922 GPS stations. Our results show that a surge in GPS-derived IWV occurred at least six hours prior to the landfall of two major hurricanes (Harvey and Irma) that struck the Gulf and East Coasts of the USA in 2017. We observed enhanced IWV, in particular, for the two hurricanes landfall locations. The observed variations exhibit a correlation with the precipitation value constructed from GPM/IMERG satellite mission coinciding with hurricane storm front passage. We used GPS-IWV data as inputs for spaghetti line plots for our path predictions, helping us predict the paths of Hurricanes Harvey and Irma. Hence, a directly estimable zenith wet delay sourced from GPS that has not been previously reported can serve as an additional resource for improving the monitoring of hurricane paths.


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