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Hongli Wang authored and/or contributed to the following articles/publications.
Background error covariance (BEC) plays a key role in variational data assimilation systems. The National Meteorological Center (NMC) method has been used widely to generate forecast error samples for BEC estimation. At present, most variational-based rapid update and cycling (RUC) data assimilation and forecasting systems use a fixed BEC withou...
Institution National Oceanic and Atmospheric Administration - NOAA
This study evaluates the impact of Tropospheric Airborne Meteorological Data Reporting (TAMDAR) observations on regional 24-hour forecast error reduction over the Continental United States (CONUS) domain using adjoint-based forecast sensitivity to observation (FSO) method as the diagnostic tool. The relative impact of TAMDAR observations on redu...
Institution National Oceanic and Atmospheric Administration - NOAA
A scale-dependent blending scheme for WRFDA: impact on regional weather forecasting
Due to limitation of the domain size and limited observations used in regional data assimilation and forecasting systems, regional forecasts suffer a general deficiency in effectively representing large-scale features such as those in global analyses and forecasts. In this paper, a scale-dependent blending scheme using a low-pass Raymond tangent...
Institutions National Center for Atmospheric Research - NCAR National Oceanic and Atmospheric Administration - NOAA
In this study, a multi-time-scale four-dimensional variational data assimilation (MTS-4DVar) scheme is developed and applied to the assimilation of radar observations. The MTS-4DVar employs multi-time windows with various time-lengths in the framework of incremental 4DVar in WRFDA (Weather Research and Forecasting Data Assimilation). The objecti...
Institutions National Oceanic and Atmospheric Administration - NOAA National Center for Atmospheric Research - NCAR
Field operations and data impact studies examine how observations from high-altitude unmanned aircraft can improve forecasts of tropical cyclones and other high-impact weather events. The National Oceanic and Atmospheric Administration’s (NOAA) Sensing Hazards with Operational Unmanned Technology (SHOUT) project evaluated the ability of obser...
Institution National Oceanic and Atmospheric Administration - NOAA
Few studies have examined the forecast uncertainties brought about from varying aircraft flight track patterns in targeted observations for extratropical winter storms. To examine the degree of uncertainty in downstream forecasts caused by different aircraft flight patterns, a series of observing system simulation experiments (OSSEs) are perform...
Institution National Oceanic and Atmospheric Administration - NOAA
The background error covariance ( B ) behaves differently and needs to be carefully defined in cloudy areas due to larger uncertainties caused by the models’ inability to correctly represent complex physical processes. This study proposes a new cloud-dependent B strategy by adaptively adjusting the hydrometeor-included B in the cloudy ...
Severe weather events can have a significant impact on local communities because of the loss of life and property. Forecast busts associated with high-impact weather events have been attributed to initial condition errors over data-sparse regions, such as the Pacific Ocean. Numerous flight campaigns have found that targeted observations over the...
A forecast sensitivity to initial perturbation (FSIP) analysis tool for the WRF Model was developed. The tool includes two modules respectively based on the conditional nonlinear optimal perturbation (CNOP) method and the first singular vector (FSV) method. The FSIP tool can be used to identify regions of sensitivity for targeted observation res...
Institution National Oceanic and Atmospheric Administration - NOAA
Assimilation of wind speed and direction observations: results from real observation experiments
The assimilation of wind observations in the form of speed and direction (asm_sd) by the Weather Research and Forecasting Model Data Assimilation System (WRFDA) was performed using real data and employing a series of cycling assimilation experiments for a 2-week period, as a follow-up for an idealised post hoc assimilation experiment. The satell...
Institution National Center for Atmospheric Research - NCAR
A blending method to merge the NCEP global analysis with the regional analysis from the WRF variational data assimilation system is implemented using a spatial filter for the purpose of initializing the Typhoon WRF (TWRF) Model, which has been in operation at Taiwan’s Central Weather Bureau (CWB) since 2010. The blended analysis is weighted towa...
Ensemble transform sensitivity method for adaptive observations
The Ensemble Transform (ET) method has been shown to be useful in providing guidance for adaptive observation deployment. It predicts forecast error variance reduction for each possible deployment using its corresponding transformation matrix in an ensemble subspace. In this paper, a new ET-based sensitivity (ETS) method, which calculates the gr...
Institution National Oceanic and Atmospheric Administration - NOAA
Ensemble Transform Sensitivity Method for Target Observations: An OSSE Case Study
Unmanned aerial system (UAS) for improving forecast accuracy of high-impact weather systems has been studied under the Sensing Hazards with Operational Unmanned Technology (SHOUT) project in the NOAA joint OSSE system. Due to the limited number of dropsondes, adaptive observation schemes have to be considered in these experiments in order to ful...
Institution National Oceanic and Atmospheric Administration - NOAA
The impacts of AMSU-A and IASI (Infrared Atmospheric Sounding Interferometer) radiances assimilation on the prediction of typhoons Vicente and Saola (2012) are studied by using the ensemble transform Kalman filter/three-dimensional variational (ETKF/3DVAR) Hybrid system for the Weather Research and Forecasting (WRF) model. The experiment without...
Institution National Center for Atmospheric Research - NCAR
Inhomogeneous Background Error Modeling for WRF-Var Using the NMC Method
Background error modeling plays a key role in a variational data assimilation system. The National Meteorological Center (NMC) method has been widely used in variational data assimilation systems to generate a forecast error ensemble from which the climatological background error covariance can be modeled. In this paper, the characteristics of t...
Institution National Center for Atmospheric Research - NCAR
Variational Assimilation of Cloud Liquid/Ice Water Path and its Impact on NWP
Analysis of the cloud components in numerical weather prediction models using advanced data assimilation techniques has been a prime topic in recent years. In this research, the variational data assimilation (DA) system for the Weather Research and Forecasting (WRF) model (WRFDA) is further developed to assimilate satellite cloud products that w...
Institution National Center for Atmospheric Research - NCAR
Variational Assimilation of Cloud Liquid/Ice Water Path and its Impact on NWP
Analysis of the cloud components in numerical weather prediction models using advanced data assimilation techniques has been a prime topic in recent years. In this study, analysis of hydrometeors for the Weather Research and Forecasting (WRF) model and its impact on short-term regional numerical weather prediction are presented. Variational data...
The National Oceanic and Atmospheric Administration’s (NOAA) Sensing Hazards with Operational Unmanned Technology (SHOUT) project evaluated the ability of observations from high-altitude unmanned aircraft to improve forecasts of high-impact weather events like tropical cyclones or mitigate potential degradation of forecasts in the event of a fut...
Institutions Earth System Research Laboratory - ESRL National Oceanic and Atmospheric Administration - NOAA