A5101598362- Meteorological Phenomena and Simulations
- Climate variability and models
- Tropical and Extratropical Cyclones Research
- Precipitation Measurement and Analysis
- Wind and Air Flow Studies
- Atmospheric aerosols and clouds
- Ocean Waves and Remote Sensing
- Atmospheric and Environmental Gas Dynamics
- Oceanographic and Atmospheric Processes
- Geophysics and Gravity Measurements
- Plant Water Relations and Carbon Dynamics
- Hydrology and Watershed Management Studies
- Reservoir Engineering and Simulation Methods
- Radio Wave Propagation Studies
- Seismic Imaging and Inversion Techniques
- Hydrological Forecasting Using AI
- Image and Signal Denoising Methods
- Cryospheric studies and observations
- 3D Shape Modeling and Analysis
- Air Traffic Management and Optimization
- Calibration and Measurement Techniques
- Icing and De-icing Technologies
- Cruise Tourism Development and Management
- Market Dynamics and Volatility
- Human Pose and Action Recognition
University of Oklahoma
2016-2025
Zhejiang Sci-Tech University
2024
Université Claude Bernard Lyon 1
2023
Université Gustave Eiffel
2023
Zhoushan Hospital
2020
NSF National Center for Atmospheric Research
2019
Microscale (United States)
2019
Research Manitoba
2019
University of Manitoba
2019
Mesoscale & Microscale Meteorology Laboratory
2019
Abstract A hybrid ensemble transform Kalman filter–three-dimensional variational data assimilation (ETKF–3DVAR) system for the Weather Research and Forecasting (WRF) Model is introduced. The based on existing WRF 3DVAR. Unlike 3DVAR, which utilizes a simple, static covariance model to estimate forecast-error statistics, combines covariances with complex, flow-dependent statistics. Ensemble are incorporated by using extended control variable method during minimization. perturbations...
Abstract An ensemble Kalman filter–variational hybrid data assimilation system based on the gridpoint statistical interpolation (GSI) three-dimensional variational (3DVar) was developed. The performance of investigated using National Centers for Environmental Prediction (NCEP) Global Forecast System model. Experiments covered a 6-week Northern Hemisphere winter period. Both control and forecasts were run at same, reduced resolution. Operational conventional satellite observations along with...
Abstract The central Great Plains region in North America has a nocturnal maximum warm-season precipitation. Much of this precipitation comes from organized mesoscale convective systems (MCSs). This is counterintuitive the sense that activity over out phase with local generation CAPE by solar heating surface. lower troposphere environment typically characterized low-level jet (LLJ) just above stable boundary layer (SBL), and available potential energy (CAPE) values peak SBL, resulting...
The ensemble transform Kalman filter (ETKF) forecast scheme is introduced and compared with both a simple masked breeding scheme. Instead of directly multiplying each perturbation constant or regional rescaling factor as in the form schemes, ETKF transforms perturbations into analysis by transformation matrix. This matrix chosen to ensure that ensemble-based error covariance would be equal true if raw were data assimilation optimal. For small ensembles (∼100), computational expense...
New methods to center the initial ensemble perturbations on analysis are introduced and compared with commonly used centering method of positive–negative paired perturbations. In new method, one linearly dependent perturbation is added a set independent ensure that sum equals zero; covariance calculated from equal error estimated by perturbations, all equally likely. The illustrated applying it transform Kalman filter (ETKF) forecast scheme, resulting called spherical simplex ETKF ensemble....
The NOAA Hazardous Weather Testbed (HWT) conducts annual spring forecasting experiments organized by the Storm Prediction Center and National Severe Storms Laboratory to test evaluate emerging scientific concepts technologies for improved analysis prediction of hazardous mesoscale weather. A primary goal is accelerate transfer promising new tools from research operations through use intensive real-time experimental evaluation activities conducted during early summer convective storm period....
Abstract The hybrid ensemble transform Kalman filter–three-dimensional variational data assimilation (ETKF–3DVAR) system developed for the Weather Research and Forecasting (WRF) Model was further tested with real observations, as a follow-up observation simulation experiment (OSSE) conducted in Part I. A domain encompassing North America considered. Because of limited computational resources large number experiments conducted, forecasts analyses employed relatively coarse grid spacing (200...
Abstract Hybrid ensemble–three-dimensional variational analysis schemes incorporate flow-dependent, ensemble-estimated background-error covariances into the three-dimensional data assimilation (3DVAR) framework. Typically 3DVAR covariance estimate is assumed to be stationary, nearly homogeneous, and isotropic. A hybrid scheme can achieved by 1) directly replacing term in cost function a linear combination of original with ensemble or 2) through augmenting state vector another set control...
Abstract Gridpoint statistical interpolation (GSI), a three-dimensional variational data assimilation method (3DVAR) has been widely used in operations and research numerical weather prediction. The operational GSI uses static background error covariance, which does not reflect the flow-dependent statistics. Incorporating ensemble covariance provides natural way to estimate manner. Different from other 3DVAR-based hybrid systems that are preconditioned on square root of commonly minimization...
Probabilistic quantitative precipitation forecasts (PQPFs) from the storm-scale ensemble forecast system run by Center for Analysis and Prediction of Storms during spring 2009 are evaluated using area under relative operating characteristic curve (ROC area). ROC area, which measures discriminating ability, is examined size n 1 to 17 members spatial scales ranging 4 200 km. Expectedly, incremental gains in skill decrease with increasing n. Significance tests comparing areas each those full...
Abstract A four-dimensional (4D) ensemble–variational data assimilation (DA) system (4DEnsVar) was developed, building upon the infrastructure of gridpoint statistical interpolation (GSI)-based hybrid DA system. 4DEnsVar used ensemble perturbations valid at multiple time periods throughout window to estimate 4D error covariances during variational minimization, avoiding tangent linear and adjoint forecast model. The formulation its implementation in GSI described. performance investigated by...
Abstract An enhanced version of the hybrid ensemble–three-dimensional variational data assimilation (3DVAR) system for Weather Research and Forecasting Model (WRF) is applied to radial velocity (Vr) from two coastal Surveillance Radar-1988 Doppler (WSR-88D) radars prediction Hurricane Ike (2008) before during its landfall. In this system, flow-dependent ensemble covariance incorporated into cost function using extended control variable method. The analysis generated by updating each forecast...
Abstract A GSI-based data assimilation (DA) system, including three-dimensional variational (3DVar) and ensemble Kalman filter (EnKF), is extended to the multiscale of both meso- synoptic-scale observation networks convective-scale radar reflectivity velocity observations. EnKF 3DVar are systematically compared in this context better understand impacts differences between DA techniques on analyses at multiple scales subsequent precipitation forecasts. Averaged over 10 diverse cases, 8-h...
Abstract A GSI-based EnVar data assimilation system is extended to directly assimilate radar reflectivity initialize convective-scale forecasts. When hydrometeor mixing ratios are used as state variables (method ratio), large differences of the cost function gradients with respect small and wind prevent efficient convergence. Using logarithmic logarithm) fixes this problem, but generates spuriously increments partly due transform from space. The tangent linear operators further contributes...
Abstract A hybrid ensemble transform Kalman filter (ETKF)–optimum interpolation (OI) analysis scheme is described and compared with an square root (EnSRF) scheme. two-layer primitive equation model was used under perfect-model assumptions. simplified observation network used, the OI method utilized a static background error covariance constructed from large inventory of historical forecast errors. The updated mean using hybridized background-error covariance. perturbations in were by ETKF...
Abstract Forecasts generated by the Center for Analysis and Prediction of Storms with 1- 4-km grid spacing using Advanced Research Weather Forecasting Model (ARW-WRF; ARW1 ARW4, respectively) 2009–11 NOAA Hazardous Testbed Spring Experiments are compared verified. Object-based measures, including average values object attributes, object-based threat score (OTS), median maximum interest (MMI) used verification. Verification was first performed against observations at scales resolvable each...
Abstract A coupled ensemble square root filter–three-dimensional ensemble-variational hybrid (EnSRF–En3DVar) data assimilation (DA) system is developed for the operational Rapid Refresh (RAP) forecasting system. The En3DVar employs extended control variable method, and built on NCEP gridpoint statistical interpolation (GSI) three-dimensional variational (3DVar) framework. It with an EnSRF RAP, which provides perturbations. Recursive filters (RF) are used to localize covariance in both...
Abstract Tropical cyclone (TC) outflow and its relationship to TC intensity change structure were investigated in the Office of Naval Research Cyclone Intensity (TCI) field program during 2015 using dropsondes deployed from innovative new High-Definition Sounding System (HDSS) remotely sensed observations Hurricane Imaging Radiometer (HIRAD), both on board NASA WB-57 that flew lower stratosphere. Three noteworthy hurricanes intensively observed with unprecedented horizontal resolution:...
© 2023 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses). Corresponding author: Jerald A. Brotzge, jerald.brotzge@wku.edu
A new method of combining dynamical and statistical ensembles for the purpose improving ensemble reliability underdispersive is introduced. The involves adding independent sets N random four-dimensional ‘dressing’ perturbations to each K members a forecast obtain an N×K dressed ensemble. mathematically constrains stochastic process used generate dressing so that it removes seasonally averaged errors in second moment measures originally ensembles. random-number generator experiment with...
Abstract A hybrid ensemble transform Kalman filter (ETKF)–three-dimensional variational data assimilation (3DVAR) system developed for the Weather Research and Forecasting Model (WRF) was studied forecasts of tracks two major hurricanes, Ike Gustav, in 2008 over Gulf Mexico. The impacts flow-dependent covariance generated by ETKF were revealed comparing forecasts, analyses, analysis increments method with those 3DVAR that used static background covariance. root-mean-square errors track (DA)...
Abstract Multiscale convection-allowing precipitation forecast perturbations are examined for two forecasts and systematically over 34 out to 30-h lead time using Haar Wavelet decomposition. Two small-scale initial condition (IC) perturbation methods compared the larger-scale IC physics in an experimental ensemble. For a driven primarily by synoptic-scale baroclinic disturbance, resulted little energy on medium large scales, (LGPH) after first few hours. However, case where convection at...
Abstract Neighborhood and object-based probabilistic precipitation forecasts from a convection-allowing ensemble are verified calibrated. Calibration methods include logistic regression, one- two-parameter reliability-based calibration, cumulative distribution function (CDF)-based bias adjustment. Newly proposed for the occurrence of forecast object derived percentage members with matching object. Verification calibration single- multimodel subensembles performed to explore effect using...
Abstract The impacts of multiscale flow-dependent initial condition (IC) perturbations for storm-scale ensemble forecasts midlatitude convection are investigated using perfect-model observing system simulation experiments. Several diverse cases used to quantitatively and qualitatively understand the different IC on forecast skill. Scale dependence results is assessed by evaluating 2-h reflectivity separately from hourly accumulated mesoscale precipitation forecasts. Forecasts initialized...
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 EnKF are used to provide flow‐dependent error covariance be ingested GSI using control variable method. then applied assimilate airborne radar data. In this article, newly developed HWRF capable of assimilating observations introduced. impact variously estimated...