Evaluation of the Four-Dimensional Ensemble-Variational Hybrid Data Assimilation with Self-Consistent Regional Background Error Covariance for Improved Hurricane Intensity Forecasts
Abstract
The feasibility of a hurricane initialization framework based on the Gridpoint Statistical Interpolation (GSI)-based four-dimensional ensemble-variational (GSI-4DEnVar) hybrid data assimilation system for the Hurricane Weather Research and Forecasting model (HWRF) model is evaluated in this study. The system considers the temporal evolution of error covariances via the use of four-dimensional ensemble perturbations that are provided by high-resolution, self-consistent HWRF ensemble forecasts. It is different from the configuration of the GSI-based three-dimensional ensemble-variational (GSI-3DEnVar) hybrid data assimilation system, similar to that used in the operational HWRF, which employs background error covariances provided by coarser-resolution global ensembles from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) ensemble Kalman filtering data assimilation system. In addition, our proposed initialization framework discards the empirical intensity correction in the vortex initialization package that is employed by the GSI-3DEnVar initialization framework in operational HWRF. Data assimilation and numerical simulation experiments for Hurricanes Joaquin (2015), Patricia (2015), and Matthew (2016) are conducted during their intensity changes. The impacts of two initialization frameworks on the HWRF analyses and forecasts are compared. It is found that GSI-4DEnVar leads to a reduction in track, minimum sea level pressure (MSLP), and maximum surface wind (MSW) forecast errors in allmore »
- Authors:
-
- Univ. of Utah, Salt Lake City, UT (United States). Dept. of Atmospheric Sciences; Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Univ. of Utah, Salt Lake City, UT (United States). Dept. of Atmospheric Sciences
- Publication Date:
- Research Org.:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Sponsoring Org.:
- USDOE Laboratory Directed Research and Development (LDRD) Program; NOAA
- OSTI Identifier:
- 1686069
- Report Number(s):
- PNNL-SA-156318
Journal ID: ISSN 2073-4433
- Grant/Contract Number:
- AC05-76RL01830; NA14NWS4680025
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Atmosphere (Basel)
- Additional Journal Information:
- Journal Name: Atmosphere (Basel); Journal Volume: 11; Journal Issue: 9; Journal ID: ISSN 2073-4433
- Publisher:
- MDPI
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; GSI-3DEnVar; GSI-4DEnVar; HWRF; hurricane intensity changes; background error covariance
Citation Formats
Zhang, Shixuan, and Pu, Zhaoxia. Evaluation of the Four-Dimensional Ensemble-Variational Hybrid Data Assimilation with Self-Consistent Regional Background Error Covariance for Improved Hurricane Intensity Forecasts. United States: N. p., 2020.
Web. doi:10.3390/atmos11091007.
Zhang, Shixuan, & Pu, Zhaoxia. Evaluation of the Four-Dimensional Ensemble-Variational Hybrid Data Assimilation with Self-Consistent Regional Background Error Covariance for Improved Hurricane Intensity Forecasts. United States. https://doi.org/10.3390/atmos11091007
Zhang, Shixuan, and Pu, Zhaoxia. Mon .
"Evaluation of the Four-Dimensional Ensemble-Variational Hybrid Data Assimilation with Self-Consistent Regional Background Error Covariance for Improved Hurricane Intensity Forecasts". United States. https://doi.org/10.3390/atmos11091007. https://www.osti.gov/servlets/purl/1686069.
@article{osti_1686069,
title = {Evaluation of the Four-Dimensional Ensemble-Variational Hybrid Data Assimilation with Self-Consistent Regional Background Error Covariance for Improved Hurricane Intensity Forecasts},
author = {Zhang, Shixuan and Pu, Zhaoxia},
abstractNote = {The feasibility of a hurricane initialization framework based on the Gridpoint Statistical Interpolation (GSI)-based four-dimensional ensemble-variational (GSI-4DEnVar) hybrid data assimilation system for the Hurricane Weather Research and Forecasting model (HWRF) model is evaluated in this study. The system considers the temporal evolution of error covariances via the use of four-dimensional ensemble perturbations that are provided by high-resolution, self-consistent HWRF ensemble forecasts. It is different from the configuration of the GSI-based three-dimensional ensemble-variational (GSI-3DEnVar) hybrid data assimilation system, similar to that used in the operational HWRF, which employs background error covariances provided by coarser-resolution global ensembles from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) ensemble Kalman filtering data assimilation system. In addition, our proposed initialization framework discards the empirical intensity correction in the vortex initialization package that is employed by the GSI-3DEnVar initialization framework in operational HWRF. Data assimilation and numerical simulation experiments for Hurricanes Joaquin (2015), Patricia (2015), and Matthew (2016) are conducted during their intensity changes. The impacts of two initialization frameworks on the HWRF analyses and forecasts are compared. It is found that GSI-4DEnVar leads to a reduction in track, minimum sea level pressure (MSLP), and maximum surface wind (MSW) forecast errors in all of the HWRF simulations, compared with the GSI-3DEnVar initialization framework. With assimilating high-resolution observations within the hurricane inner-core region, GSI-4DEnVar can produce the initial hurricane intensity reasonably well without the empirical vortex intensity correction. Further diagnoses with Hurricane Joaquin indicate that GSI-4DEnVar can significantly alleviate the imbalances in the initial conditions and enhance the performance of the data assimilation and subsequent hurricane intensity and precipitation forecasts},
doi = {10.3390/atmos11091007},
journal = {Atmosphere (Basel)},
number = 9,
volume = 11,
place = {United States},
year = {Mon Sep 21 00:00:00 EDT 2020},
month = {Mon Sep 21 00:00:00 EDT 2020}
}
Figures / Tables:
Works referenced in this record:
Achievement of USWRP Hurricane Landfall Research Goal
journal, May 2005
- Elsberry, Russell L.
- Bulletin of the American Meteorological Society, Vol. 86, Issue 5
Performance of convection-permitting hurricane initialization and prediction during 2008-2010 with ensemble data assimilation of inner-core airborne Doppler radar observations: HURRICANE INITIALIZATION AND PREDICTION
journal, August 2011
- Zhang, Fuqing; Weng, Yonghui; Gamache, John F.
- Geophysical Research Letters, Vol. 38, Issue 15
Tropical Cyclone Lightning and Rapid Intensity Change
journal, June 2012
- DeMaria, Mark; DeMaria, Robert T.; Knaff, John A.
- Monthly Weather Review, Vol. 140, Issue 6
Comparison of Hybrid-4DEnVar and Hybrid-4DVar Data Assimilation Methods for Global NWP
journal, January 2015
- Lorenc, Andrew C.; Bowler, Neill E.; Clayton, Adam M.
- Monthly Weather Review, Vol. 143, Issue 1
GSI-based ensemble-variational hybrid data assimilation for HWRF for hurricane initialization and prediction: impact of various error covariances for airborne radar observation assimilation: GSI-based Hybrid DA for Hurricane-WRF Using Airborne Radar
journal, November 2016
- Lu, Xu; Wang, Xuguang; Li, Yongzuo
- Quarterly Journal of the Royal Meteorological Society, Vol. 143, Issue 702
Four-dimensional ensemble-variational data assimilation for global deterministic weather prediction
journal, January 2013
- Buehner, M.; Morneau, J.; Charette, C.
- Nonlinear Processes in Geophysics, Vol. 20, Issue 5
Improving Hurricane Analyses and Predictions with TCI, IFEX Field Campaign Observations, and CIMSS AMVs Using the Advanced Hybrid Data Assimilation System for HWRF. Part II: Observation Impacts on the Analysis and Prediction of Patricia (2015)
journal, March 2020
- Lu, Xu; Wang, Xuguang
- Monthly Weather Review, Vol. 148, Issue 4
Incorporating Ensemble Covariance in the Gridpoint Statistical Interpolation Variational Minimization: A Mathematical Framework
journal, July 2010
- Wang, Xuguang
- Monthly Weather Review, Vol. 138, Issue 7
GSI-Based Four-Dimensional Ensemble–Variational (4DEnsVar) Data Assimilation: Formulation and Single-Resolution Experiments with Real Data for NCEP Global Forecast System
journal, September 2014
- Wang, Xuguang; Lei, Ting
- Monthly Weather Review, Vol. 142, Issue 9
Accuracy of Atlantic and Eastern North Pacific Tropical Cyclone Intensity Forecast Guidance
journal, August 2007
- Elsberry, Russell L.; Lambert, Tara D. B.; Boothe, Mark A.
- Weather and Forecasting, Vol. 22, Issue 4
Reexamination of Tropical Cyclone Wind–Pressure Relationships
journal, February 2007
- Knaff, John A.; Zehr, Raymond M.
- Weather and Forecasting, Vol. 22, Issue 1
Impact of Enhanced Atmospheric Motion Vectors on HWRF Hurricane Analyses and Forecasts with Different Data Assimilation Configurations
journal, May 2018
- Zhang, Shixuan; Pu, Zhaoxia; Velden, Christopher
- Monthly Weather Review, Vol. 146, Issue 5
An OSSE-Based Evaluation of Hybrid Variational–Ensemble Data Assimilation for the NCEP GFS. Part II: 4DEnVar and Hybrid Variants
journal, February 2015
- Kleist, Daryl T.; Ide, Kayo
- Monthly Weather Review, Vol. 143, Issue 2
Scientific Documentation for the NMM Solver
text, January 2010
- Janjic, Zavisa; Gall, Robert; Pyle, Matthew
- UCAR/NCAR
Influence of the Self-Consistent Regional Ensemble Background Error Covariance on Hurricane Inner-Core Data Assimilation with the GSI-Based Hybrid System for HWRF
journal, November 2016
- Pu, Zhaoxia; Zhang, Shixuan; Tong, Mingjing
- Journal of the Atmospheric Sciences, Vol. 73, Issue 12
Evaluation of Storm Structure from the Operational HWRF during 2012 Implementation
journal, November 2014
- Tallapragada, Vijay; Kieu, Chanh; Kwon, Young
- Monthly Weather Review, Vol. 142, Issue 11
NOAA'S Hurricane Intensity Forecasting Experiment: A Progress Report
journal, June 2013
- Rogers, Robert; Aberson, Sim; Aksoy, Altug
- Bulletin of the American Meteorological Society, Vol. 94, Issue 6
Numerical Simulation of Rapid Weakening of Hurricane Joaquin with Assimilation of High-Definition Sounding System Dropsondes during the Tropical Cyclone Intensity Experiment: Comparison of Three- and Four-Dimensional Ensemble–Variational Data Assimilation
journal, May 2019
- Zhang, Shixuan; Pu, Zhaoxia
- Weather and Forecasting, Vol. 34, Issue 3
Numerical simulation of the rapid intensification of Hurricane Katrina (2005): Sensitivity to boundary layer parameterization schemes
journal, April 2017
- Liu, Jianjun; Zhang, Feimin; Pu, Zhaoxia
- Advances in Atmospheric Sciences, Vol. 34, Issue 4
Improved Tropical-Cyclone Flight-Level Wind Estimates Using Routine Infrared Satellite Reconnaissance
journal, February 2015
- Knaff, John A.; Longmore, Scott P.; DeMaria, Robert T.
- Journal of Applied Meteorology and Climatology, Vol. 54, Issue 2
The Experimental HWRF System: A Study on the Influence of Horizontal Resolution on the Structure and Intensity Changes in Tropical Cyclones Using an Idealized Framework
journal, June 2011
- Gopalakrishnan, Sundararaman G.; Marks, Frank; Zhang, Xuejin
- Monthly Weather Review, Vol. 139, Issue 6
A Preliminary Impact Study of CYGNSS Ocean Surface Wind Speeds on Numerical Simulations of Hurricanes
journal, March 2019
- Cui, Zhiqiang; Pu, Zhaoxia; Tallapragada, Vijay
- Geophysical Research Letters, Vol. 46, Issue 5
Three-Dimensional Variational Analysis with Spatially Inhomogeneous Covariances
journal, December 2002
- Wu, Wan-Shu; Purser, R. James; Parrish, David F.
- Monthly Weather Review, Vol. 130, Issue 12
GSI 3DVar-Based Ensemble–Variational Hybrid Data Assimilation for NCEP Global Forecast System: Single-Resolution Experiments
journal, October 2013
- Wang, Xuguang; Parrish, David; Kleist, Daryl
- Monthly Weather Review, Vol. 141, Issue 11
Further Improvements to the Statistical Hurricane Intensity Prediction Scheme (SHIPS)
journal, August 2005
- DeMaria, Mark; Mainelli, Michelle; Shay, Lynn K.
- Weather and Forecasting, Vol. 20, Issue 4
Figures / Tables found in this record: