An Efficient Dual-Resolution Approach for Ensemble Data Assimilation and Tests with Simulated Doppler Radar Data

2008 ◽  
Vol 136 (3) ◽  
pp. 945-963 ◽  
Author(s):  
Jidong Gao ◽  
Ming Xue
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Radial Velocity ◽  
Computational Cost ◽  
Radar Data ◽  
Horizontal Resolution ◽  
Velocity Data ◽  
Background Error ◽  
Cross Covariance ◽  
Radial Velocity Data

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.

scholarly journals Assimilation of Radial Velocity from Coastal NEXRAD into HWRF for Improved Forecasts of Landfalling Hurricanes

2021 ◽  
Author(s):  
Ying Wang ◽  
Zhaoxia Pu
Keyword(s):  
Data Assimilation ◽  
Radial Velocity ◽  
Radar Data ◽  
Asymmetric Structure ◽  
Velocity Data ◽  
Background Error ◽  
Convective Systems ◽  
Forecasting System ◽  
Environmental Prediction ◽  
Radial Velocity Data

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.

Comparisons of Hybrid En3DVar with 3DVar and EnKF for Radar Data Assimilation: Tests with the 10 May 2010 Oklahoma Tornado Outbreak

2021 ◽  
Vol 149 (1) ◽  
pp. 21-40
Author(s):  
Rong Kong ◽  
Ming Xue ◽  
Chengsi Liu ◽  
Youngsun Jung
Keyword(s):  
Data Assimilation ◽  
Radial Velocity ◽  
Forecast Error ◽  
Radar Data ◽  
Separate Analysis ◽  
Background Error ◽  
Mixing Ratios ◽  
Error Covariance ◽  
Radial Velocity Data ◽  
Made In

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.

scholarly journals Multipass Objective Analyses of Doppler Radar Data

2008 ◽  
Vol 25 (10) ◽  
pp. 1845-1858 ◽  
Author(s):  
Mario Majcen ◽  
Paul Markowski ◽  
Yvette Richardson ◽  
David Dowell ◽  
Joshua Wurman
Keyword(s):  
Radial Velocity ◽  
Computational Cost ◽  
Three Dimensional ◽  
Radar Data ◽  
Objective Analysis ◽  
Small Scale ◽  
Velocity Data ◽  
Wind Fields ◽  
Single Pass ◽  
Radial Velocity Data

Abstract This note assesses the improvements in dual-Doppler wind syntheses by employing a multipass Barnes objective analysis in the interpolation of radial velocities to a Cartesian grid, as opposed to a more typical single-pass Barnes objective analysis. Steeper response functions can be obtained by multipass objective analyses; that is, multipass objective analyses are less damping at well-resolved wavelengths (e.g., 8–20Δ, where Δ is the data spacing) than single-pass objective analyses, while still suppressing small-scale (<4Δ) noise. Synthetic dual-Doppler data were generated from a three-dimensional numerical simulation of a supercell thunderstorm in a way that emulates the data collection by two mobile radars. The synthetic radial velocity data from a pair of simulated radars were objectively analyzed to a grid, after which the three-dimensional wind field was retrieved by iteratively computing the horizontal divergence and integrating the anelastic mass continuity equation. Experiments with two passes and three passes of the Barnes filter were performed, in addition to a single-pass objective analysis. Comparison of the analyzed three-dimensional wind fields to the model wind fields suggests that multipass objective analysis of radial velocity data prior to dual-Doppler wind synthesis is probably worth the added computational cost. The improvements in the wind syntheses derived from multipass objective analyses are even more apparent for higher-order fields such as vorticity and divergence, and for trajectory calculations and pressure/buoyancy retrievals.

scholarly journals The inhomogeneous wind of the LBV candidate Cyg OB2 No.12

2010 ◽  
Vol 6 (S272) ◽  
pp. 400-401
Author(s):  
Valentina G. Klochkova ◽  
Eugene L. Chentsov ◽  
Anatoly S. Miroshnichenko
Keyword(s):  
High Resolution ◽  
Radial Velocity ◽  
Stellar Atmosphere ◽  
Time Variable ◽  
High Resolution Spectroscopy ◽  
Spectral Features ◽  
Velocity Data ◽  
Absorption Component ◽  
Hα Emission ◽  
Radial Velocity Data

AbstractWe present the results of high-resolution spectroscopy of the extremely luminous star Cyg OB2 No. 12. We identified about 200 spectral features in the range 4552–7939 Å, including the interstellar Na I, K I lines and numerous very strong DIBs, along with the He I, C II, and Si II lines. An MK spectral type we derived for the object is B4.5±0.5 Ia+. Our analysis of the radial velocity data shows the presence of a gradient in the stellar atmosphere, caused by both atmospheric expansion and matter infall onto the star. The Hα emission displays broad Thompson wings, a slightly blue-shifted P Cyg type absorption component and a time-variable core absorption. We conclude that the wind is variable in time.

scholarly journals Application of the Multigrid Method to the Two-Dimensional Doppler Radar Radial Velocity Data Assimilation

2010 ◽  
Vol 27 (2) ◽  
pp. 319-332 ◽  
Author(s):  
Wei Li ◽  
Yuanfu Xie ◽  
Shiow-Ming Deng ◽  
Qi Wang
Keyword(s):  
Data Assimilation ◽  
Radial Velocity ◽  
Multigrid Method ◽  
Doppler Radar ◽  
Wind Data ◽  
In Situ Observation ◽  
Velocity Data ◽  
Significant Information ◽  
Tangential Wind ◽  
Radial Velocity Data

Abstract In recent years, the Earth System Research Laboratory (ESRL) of the National Oceanic and Atmospheric Administration (NOAA) has developed a space and time mesoscale analysis system (STMAS), which is currently a sequential three-dimensional variational data assimilation (3DVAR) system and is developing into a sequential 4DVAR in the near future. It is implemented by using a multigrid method based on a variational approach to generate grid analyses. This study is to test how STMAS deals with 2D Doppler radar radial velocity and to what degree the 2D Doppler radar radial velocity can improve the conventional (in situ) observation analysis. Two idealized experiments and one experiment with real Doppler radar radial velocity data, handled by STMAS, demonstrated significant improvement of the conventional observation analysis. Because the radar radial wind data can provide additional wind information (even it is incomplete: e.g., missing tangential wind vector), the analyses by assimilating both radial wind data and conventional data showed better results than those by assimilating only conventional data. Especially in the case of sparse conventional data, radar radial wind data can provide significant information and improve the analyses considerably.

scholarly journals High resolution assimilation of IASI ozone data with a global CTM

2011 ◽  
Vol 11 (10) ◽  
pp. 29357-29406 ◽  
Author(s):  
B. Pajot ◽  
S. Massart ◽  
D. Cariolle ◽  
A. Piacentini ◽  
O. Pannekoucke ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Correlation Length ◽  
Computational Cost ◽  
Horizontal Resolution ◽  
Small Scale ◽  
Length Scale ◽  
Pixel Size ◽  
Direct Model ◽  
Scale Structures

Abstract. The pixel size of the Infrared Atmospheric Sounding Interferometer (IASI) remote sensor is much smaller than the horizontal grid size of current Chemical Transport Models (CTMs). In order to assimilate the maximum of information from the IASI retrievals, we have increased the horizontal resolution of our model MOCAGE to be consistent with the IASI pixel size. Experiments are carried out with the Valentina data assimilation system using the standard and the high resolution versions of the model. Two resolutions of the horizontal Gaussian grid have been used for the model: with a T42 and a T170 triangular truncations. Our study is based on the combination of data from the IASI instrument and from the Microwave Limb Sounder (MLS), since this latter dataset allows the information to be spread through the whole atmospheric columns at a low computational cost. Two datasets of ozone super-observations have been constructed by averaging the IASI data on the two model grids. Direct model simulations without data assimilation first show that the increase of the horizontal resolution modifies the ozone smallest scale structures as well as the ozone meridional distribution. This modification results from a better representation of the vertical velocity with the T170 configuration. When the ozone assimilation is performed there is less influence of the horizontal resolution of the model. Nevertheless, in a general way, comparisons with independent data show large reductions of the ozone standard deviations when the resolution is increased. When the ozone assimilation is performed with the high resolution dataset, the high resolution model does not improve the ozone analysis compared to the one obtained with the same model resolution but with the low resolution IASI dataset. This result is due to the difficulty to combine IASI data and MLS data. For assimilating IASI data at high resolution the horizontal correlation length-scale has to be decreased to catch the small scale structures present in the dataset. By doing so the influence of the coarser resolution MLS data is decreased and part of the information brought on the vertical shape of the ozone profile is lost. It is concluded that it is essential to add information on the vertical distribution of ozone column when the IASI data is assimilated at a resolution close to the pixel size. Using IASI averaging kernels would likely improve the simulations, but the computational cost would be much higher. Alternatively, better results might be obtained by a careful tuning of the horizontal correlation length-scale.

scholarly journals Chemical abundances of three new Ba stars from the Keck/HIRES spectra

2021 ◽  
Vol 21 (11) ◽  
pp. 278
Author(s):  
Shuai Liu ◽  
Liang Wang ◽  
Jian-Rong Shi ◽  
Zhen-Yu Wu ◽  
Hong-Liang Yan ◽  
...  
Keyword(s):  
High Resolution ◽  
Radial Velocity ◽  
Parameter Space ◽  
Thin Disk ◽  
High Signal ◽  
Velocity Data ◽  
Signal To Noise ◽  
Chemical Abundances ◽  
Radial Velocity Data

Abstract Based on high resolution, high signal-to-noise (S/N) ratio spectra from Keck/HIRES, we have determined abundances of 20 elements for 18 Ba candidates. The parameter space of these stars is in the range of 4880 ≤ T eff ≤ 6050 K, 2.56 ≤ log g ≤ 4.53 dex and − 0.27 ≤ [Fe/H] ≤ 0.09 dex. It is found that four of them can be identified as Ba stars with [s/Fe] > 0.25 dex (s: Sr, Y, Zr, Ba, La, Ce and Nd), and three of them are newly discovered, which include two Ba giants (HD 16178 and HD 22233) and one Ba subgiant (HD 2946). Our results show that the abundances of α, odd and iron-peak elements (O, Na, Mg, Al, Si, Ca, Sc, Ti, Mn, Ni and Cu) for our program stars are similar to those of the thin disk, while the distribution of [hs/ls] (hs: Ba, La, Ce and Nd, ls: Sr, Y and Zr) ratios of our Ba stars is similar to those of the known Ba objects. None of the four Ba stars show clear enhancement in carbon including the known CH subgiant HD 4395. It is found that three of the Ba stars present clear evidence of hosting stellar or sub-stellar companions from the radial velocity data.

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