The Effects of Sampling Errors on the EnKF Assimilation of Inner-Core Hurricane Observations

2014 ◽  
Vol 142 (4) ◽  
pp. 1609-1630 ◽  
Author(s):  
Jonathan Poterjoy ◽  
Fuqing Zhang ◽  
Yonghui Weng
Keyword(s):  
Data Assimilation ◽  
Hurricane Katrina ◽  
Inner Core ◽  
Doppler Radar ◽  
Mesoscale Model ◽  
Outer Core ◽  
State Variables ◽  
Sampling Errors ◽  
Relaxation Coefficient ◽  
Airborne Doppler Radar

Abstract Atmospheric data assimilation methods that estimate flow-dependent forecast statistics from ensembles are sensitive to sampling errors. This sensitivity is investigated in the context of vortex-scale hurricane data assimilation by cycling an ensemble Kalman filter to assimilate observations with a convection-permitting mesoscale model. In a set of numerical experiments, airborne Doppler radar observations are assimilated for Hurricane Katrina (2005) using an ensemble size that ranges from 30 to 300 members, and a varying degree of covariance inflation through relaxation to the prior. The range of ensemble sizes is shown to produce variations in posterior storm structure that persist for days in deterministic forecasts, with the most substantial differences appearing in the vortex outer-core wind and pressure fields. Ensembles with 60 or more members converge toward similar axisymmetric and asymmetric inner-core solutions by the end of the cycling, while producing qualitatively similar sample correlations between the state variables. Though covariance relaxation has little impact on model variables far from the observations, the structure of the inner-core vortex can benefit from a more optimal tuning of the relaxation coefficient. Results from this study provide insight into how sampling errors may affect the performance of an ensemble hurricane data assimilation system during cycling.

scholarly journals Verification of a High-Resolution Model Forecast Using Airborne Doppler Radar Analysis during the Rapid Intensification of Hurricane Guillermo

2010 ◽  
Vol 49 (4) ◽  
pp. 807-820 ◽  
Author(s):  
X. Zou ◽  
Yonghui Wu ◽  
Peter Sawin Ray
Keyword(s):  
High Resolution ◽  
Inner Core ◽  
Doppler Radar ◽  
Mesoscale Model ◽  
Radial Profile ◽  
Initial Time ◽  
Rapid Intensification ◽  
Model Forecast ◽  
Research Division ◽  
Airborne Doppler Radar

Abstract The NOAA Hurricane Research Division (HRD) P-3 aircraft provided airborne radar observations during the period of rapid intensification of Hurricane Guillermo on 2 August 1997. The inner core structure and evolution of Hurricane Guillermo (1997) over a 120 km by 120 km square area, centered on the storm, was observed by the P-3 aircraft during 10 flight legs at half-hour intervals during a 6-h period from 1800 UTC 2 August to 0000 UTC 3 August 1997. A high-resolution short-term model forecast initialized at 1800 UTC 2 August 1997 was made using the fifth-generation Pennsylvania State University–NCAR nonhydrostatic, two-way interactive, movable, triply nested grid Mesoscale Model (MM5). The weak vortex at the initial time in the NCEP analysis was replaced by a tropical storm–like vortex generated by a 4D variational data assimilation (4D-Var) vortex initialization experiment. The modeled Guillermo followed the observed track with less than a 12-km track error at any time during the 6-h forecast period. The modeled eye is smaller than the observed eye and the modeled vortex is more upright than shown by the radar analysis. The minimum pressure, maximum wind (intensity), and radial profile of tangential winds are close to the radar analysis after 2–3 h of model spinup. A spectral decomposition further reveals that (i) large differences between the model simulation and radar analysis of the asymmetric features are mostly caused by azimuthal phase errors; (ii) the wavenumber 1 component dominates the asymmetric features and remains stationary within the inner core region, as is also observed by airborne Doppler radar; and (iii) although being significantly different from radar analysis, the azimuthal phase of the wavenumber 1 component of modeled reflectivity does not vary greatly with time as the radar data suggest.

Dynamics and Structure of Forecast Error Covariance in the Core of a Developing Hurricane

2011 ◽  
Vol 68 (8) ◽  
pp. 1586-1606 ◽  
Author(s):  
Jonathan Poterjoy ◽  
Fuqing Zhang
Keyword(s):  
Hurricane Katrina ◽  
Inner Core ◽  
Forecast Error ◽  
Tropical Storm ◽  
Vortex Center ◽  
State Variables ◽  
Spatial Error ◽  
Position Uncertainty ◽  
Error Covariance ◽  
Model State

Abstract An ensemble of cloud-resolving forecasts from the Weather Research and Forecasting model (WRF) was used to study error covariance for Hurricane Katrina (2005) during a 64-h period in which the storm progressed from a tropical storm to a category-4 hurricane. Spatial error covariance between hypothetical measurements and model state variables was found to be highly anisotropic, variable dependent, and ultimately determined by the underlying storm dynamics, which change dramatically over time. Early in the forecast, when Katrina passed over the southern tip of the Florida Peninsula as a highly asymmetric tropical storm, error covariance structures in the Eulerian coordinates were dominated primarily by position uncertainty, with a secondary dependence on land–air interaction, storm structure, and intensity. The ensemble error dependence on position uncertainty becomes markedly greater with increasing lead time, as diverging storm tracks cause large gradients of wind, temperature, and pressure to be concentrated farther from the mean vortex center. Ensemble variance for model state variables on storm-relative coordinates becomes increasingly symmetric about the vortex center at greater hurricane intensity. Likewise, spatial and cross-spatial correlations share a similar axisymmetric transition about the origin, while maintaining a large degree of local anisotropy with respect to the location chosen for the correlation point. Our results demonstrate the necessity of using flow-dependent error covariance for initializing a tropical cyclone with dynamically consistent inner-core structure, and provide motivation for future sensitivity experiments pertaining to model resolution and ensemble size.

An Approach of Radar Reflectivity Data Assimilation and Its Assessment with the Inland QPF of Typhoon Rusa (2002) at Landfall

2007 ◽  
Vol 46 (1) ◽  
pp. 14-22 ◽  
Author(s):  
Qingnong Xiao ◽  
Ying-Hwa Kuo ◽  
Juanzhen Sun ◽  
Wen-Chau Lee ◽  
Dale M. Barker ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Doppler Radar ◽  
Mesoscale Model ◽  
Control Variable ◽  
Three Dimensional ◽  
Radar Data ◽  
Radar Reflectivity ◽  
Mixing Ratio ◽  
Warm Rain Process ◽  
Reflectivity Data

Abstract A radar reflectivity data assimilation scheme was developed within the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) three-dimensional variational data assimilation (3DVAR) system. The model total water mixing ratio was used as a control variable. A warm-rain process, its linear, and its adjoint were incorporated into the system to partition the moisture and hydrometeor increments. The observation operator for radar reflectivity was developed and incorporated into the 3DVAR. With a single reflectivity observation, the multivariate structures of the analysis increments that included cloud water and rainwater mixing ratio increments were examined. Using the onshore Doppler radar data from Jindo, South Korea, the capability of the radar reflectivity assimilation for the landfalling Typhoon Rusa (2002) was assessed. Verifications of inland quantitative precipitation forecasting (QPF) of Typhoon Rusa (2002) showed positive impacts of assimilating radar reflectivity data on the short-range QPF.

Improved Prediction of Landfalling Tropical Cyclone in China Based on Assimilation of Radar Radial Winds with New Super-Observation Processing

2020 ◽  
Vol 35 (6) ◽  
pp. 2523-2539
Author(s):  
Jianing Feng ◽  
Yihong Duan ◽  
Qilin Wan ◽  
Hao Hu ◽  
Zhaoxia Pu
Keyword(s):  
Data Assimilation ◽  
Inner Core ◽  
Doppler Radar ◽  
Weather Prediction ◽  
Extreme Rainfall ◽  
Radar Data ◽  
Numerical Weather Prediction Model ◽  
Previous Method ◽  
Horizontal Wind ◽  
The Impact

AbstractThis work explores the impact of assimilating radial winds from the Chinese coastal Doppler radar on track, intensity, and quantitative precipitation forecasts (QPF) of landfalling tropical cyclones (TCs) in a numerical weather prediction model, focusing mainly on two aspects: 1) developing a new coastal radar super-observation (SO) processing method, namely, an evenly spaced thinning method (ESTM) that is fit for landfalling TCs, and 2) evaluating the performance of the radar radial wind data assimilation in QPFs of landfalling TCs with multiple TC cases. Compared to a previous method of generating SOs (i.e., the radially spaced thinning method), in which the density of SOs is equal within the radial space of a radar scanning volume, the SOs created by ESTM are almost evenly distributed in the horizontal grids of the model background, resulting in more observations located in the TC inner-core region being involved in SOs. The use of SOs from ESTM leads to more cyclonic wind innovation, and larger analysis increments of height and horizontal wind in the lower level in an ensemble Kalman filter data assimilation experiment with TC Mujigae (2015). Overall, forecasts of a TC’s landfalling position, intensity, and QPF are improved by radar data assimilation for all cases, including Mujigae and the other eight TCs that made landfall on the Chinese mainland in 2017. Specifically, through assimilation, TC landing position error and intensity error are reduced by 33% and 25%, respectively. The mean equitable threat score of extreme rainfall [>80 mm (3 h)−1] forecasts is doubled on average over all cases.

Predicting Hurricane Intensity and Associated Hazards: A Five-Year Real-Time Forecast Experiment with Assimilation of Airborne Doppler Radar Observations

2015 ◽  
Vol 96 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Fuqing Zhang ◽  
Yonghui Weng
Keyword(s):  
Inner Core ◽  
Doppler Radar ◽  
Surface Wind ◽  
Forecast Errors ◽  
Hurricane Intensity ◽  
Radar Observations ◽  
Intensity Forecast ◽  
Probabilistic Forecasts ◽  
Atlantic Hurricanes ◽  
Airborne Doppler Radar

Abstract Performance in the prediction of hurricane intensity and associated hazards has been evaluated for a newly developed convection-permitting forecast system that uses ensemble data assimilation techniques to ingest high-resolution airborne radar observations from the inner core. This system performed well for three of the ten costliest Atlantic hurricanes: Ike (2008), Irene (2011), and Sandy (2012). Four to five days before these storms made landfall, the system produced good deterministic and probabilistic forecasts of not only track and intensity, but also of the spatial distributions of surface wind and rainfall. Averaged over all 102 applicable cases that have inner-core airborne Doppler radar observations during 2008–2012, the system reduced the day-2-to-day-4 intensity forecast errors by 25%–28% compared to the corresponding National Hurricane Center’s official forecasts (which have seen little or no decrease in intensity forecast errors over the past two decades). Empowered by sufficient computing resources, advances in both deterministic and probabilistic hurricane prediction will enable emergency management officials, the private sector, and the general public to make more informed decisions that minimize the losses of life and property.

scholarly journals Improving the Model Convective Storm Quantitative Precipitation Nowcasting by Assimilating State Variables Retrieved from Multiple-Doppler Radar Observations

2014 ◽  
Vol 142 (11) ◽  
pp. 4017-4035 ◽  
Author(s):  
Yu-Chieng Liou ◽  
Jian-Luen Chiou ◽  
Wei-Hao Chen ◽  
Hsin-Yu Yu
Keyword(s):  
Data Assimilation ◽  
Doppler Radar ◽  
Scale Up ◽  
Three Dimensional ◽  
Radar Data ◽  
State Variables ◽  
Weather System ◽  
Additional Information ◽  
Convective Scale ◽  
Fine Resolution

Abstract This research combines an advanced multiple-Doppler radar synthesis technique with the thermodynamic retrieval method, originally proposed by Gal-Chen, and a moisture/temperature adjustment scheme, and formulates a sequential procedure. The focus is on applying this procedure to improve the model quantitative precipitation nowcasting (QPN) skill in the convective scale up to 3 hours. A series of (observing system simulation experiment) OSSE-type tests and a real case study are conducted to investigate the performance of this algorithm under different conditions. It is shown that by using the retrieved three-dimensional wind, thermodynamic, and microphysical parameters to reinitialize a fine-resolution numerical model, its QPN skill can be significantly improved. Since the Gal-Chen method requires the horizontal average properties of the weather system at each altitude, utilization of in situ radiosonde(s) to obtain this additional information for the retrieval is tested. When sounding data are not available, it is demonstrated that using the model results to replace the role played by observing devices is also a feasible choice. The moisture field is obtained through a simple, but effective, adjusting scheme and is found to be beneficial to the rainfall forecast within the first hour after the reinitialization of the model. Since this algorithm retrieves the unobserved state variables instantaneously from the wind measurements and directly uses them to reinitialize the model, fewer radar data and a shorter model spinup time are needed to correct the rainfall forecasts, in comparison with other data assimilation techniques such as four-dimensional variational data assimilation (4DVAR) or ensemble Kalman filter (EnKF) methods.

scholarly journals A Latent Heat Retrieval and Its Effects on the Intensity and Structure Change of Hurricane Guillermo (1997). Part II: Numerical Simulations

2012 ◽  
Vol 69 (11) ◽  
pp. 3128-3146 ◽  
Author(s):  
Stephen R. Guimond ◽  
Jon M. Reisner
Keyword(s):  
Numerical Simulations ◽  
Tropical Cyclones ◽  
Latent Heat ◽  
Inner Core ◽  
Doppler Radar ◽  
Model Parameters ◽  
Saturation State ◽  
Wind Structure ◽  
Tangential Wind ◽  
Airborne Doppler Radar

Abstract In Part I of this study, a new algorithm for retrieving the latent heat field in tropical cyclones from airborne Doppler radar was presented and fields from rapidly intensifying Hurricane Guillermo (1997) were shown. In Part II, the usefulness and relative accuracy of the retrievals is assessed by inserting the heating into realistic numerical simulations at 2-km resolution and comparing the generated wind structure to the radar analyses of Guillermo. Results show that using the latent heat retrievals as forcing produces very low intensity and structure errors (in terms of tangential wind speed errors and explained wind variance) and significantly improves simulations relative to a predictive run that is highly calibrated to the latent heat retrievals by using an ensemble Kalman filter procedure to estimate values of key model parameters. Releasing all the heating/cooling in the latent heat retrieval results in a simulation with a large positive bias in Guillermo’s intensity that motivates the need to determine the saturation state in the hurricane inner-core retrieval through a procedure similar to that described in Part I of this study. The heating retrievals accomplish high-quality structure statistics by forcing asymmetries in the wind field with the generally correct amplitude, placement, and timing. In contrast, the latent heating fields generated in the predictive simulation contain a significant bias toward large values and are concentrated in bands (rather than discrete cells) stretched around the vortex. The Doppler radar–based latent heat retrievals presented in this series of papers should prove useful for convection initialization and data assimilation to reduce errors in numerical simulations of tropical cyclones.

Quadrant Distribution of Tropical Cyclone Inner-Core Kinematics in Relation to Environmental Shear

2014 ◽  
Vol 71 (7) ◽  
pp. 2713-2732 ◽  
Author(s):  
Jennifer C. DeHart ◽  
Robert A. Houze ◽  
Robert F. Rogers
Keyword(s):  
Tropical Cyclone ◽  
Inner Core ◽  
Doppler Radar ◽  
Radar Data ◽  
Low Level ◽  
Strong Convection ◽  
Upper Level ◽  
Airborne Doppler Radar ◽  
The Vertical Distribution ◽  
Left Quadrant

Abstract Airborne Doppler radar data collected in tropical cyclones by National Oceanic and Atmospheric Administration WP-3D aircraft over an 8-yr period (2003–10) are used to statistically analyze the vertical structure of tropical cyclone eyewalls with reference to the deep-layer shear. Convective evolution within the inner core conforms to patterns shown by previous studies: convection initiates downshear right, intensifies downshear left, and weakens upshear. Analysis of the vertical distribution of radar reflectivity and vertical air motion indicates the development of upper-level downdrafts in conjunction with strong convection downshear left and a maximum in frequency upshear left. Intense updrafts and downdrafts both conform to the shear asymmetry pattern. While strong updrafts occur in the eyewall, intense downdrafts show far more radial variability, particularly in the upshear-left quadrant, though they concentrate along the eyewall edges. Strong updrafts are collocated with low-level inflow and upper-level outflow superimposed on the background flow. In contrast, strong downdrafts occur in association with low-level outflow and upper-level inflow.

scholarly journals Multiscale Analysis of Tropical Cyclone Kinematic Structure from Airborne Doppler Radar Composites

2012 ◽  
Vol 140 (1) ◽  
pp. 77-99 ◽  
Author(s):  
Robert Rogers ◽  
Sylvie Lorsolo ◽  
Paul Reasor ◽  
John Gamache ◽  
Frank Marks
Keyword(s):  
Inner Core ◽  
Doppler Radar ◽  
Maximum Wind ◽  
Axisymmetric Vortex ◽  
Tangential Wind ◽  
Convective Scale ◽  
Secondary Circulations ◽  
Scale Properties ◽  
Hurricane Boundary Layer ◽  
Airborne Doppler Radar

Abstract The multiscale inner-core structure of mature tropical cyclones is presented via the use of composites of airborne Doppler radar analyses. The structure of the axisymmetric vortex and the convective and turbulent-scale properties within this axisymmetric framework are shown to be consistent with many previous studies focusing on individual cases or using different airborne data sources. On the vortex scale, these structures include the primary and secondary circulations, eyewall slope, decay of the tangential wind with height, low-level inflow layer and region of enhanced outflow, radial variation of convective and stratiform reflectivity, eyewall vorticity and divergence fields, and rainband signatures in the radial wind, vertical velocity, vorticity, and divergence composite mean and variance fields. Statistics of convective-scale fields and how they vary as a function of proximity to the radius of maximum wind show that the inner eyewall edge is associated with stronger updrafts and higher reflectivity and vorticity in the mean and have broader distributions for these fields compared with the outer radii. In addition, the reflectivity shows a clear characteristic of stratiform precipitation in the outer radii and the vorticity distribution is much more positively skewed along the inner eyewall than it is in the outer radii. Composites of turbulent kinetic energy (TKE) show large values along the inner eyewall, in the hurricane boundary layer, and in a secondary region located at about 2–3 times the radius of maximum wind. This secondary peak in TKE is also consistent with a peak in divergence and in the variability of vorticity, and they suggest the presence of rainbands at this radial band.

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