scholarly journals An Attempt to Improve the Forecasting of Persistent Severe Rainfall Using the Spectral Nudging and Update Cycle Methods

2017 ◽  
Vol 32 (2) ◽  
pp. 713-723 ◽  
Author(s):  
Yanfeng Zhao ◽  
Donghai Wang ◽  
Jianjun Xu
Keyword(s):  
Large Scale ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Brier Score ◽  
Small Scale ◽  
Lead Times ◽  
Spectral Nudging ◽  
Numerical Predictions ◽  
Forecast Lead Time ◽  
Accumulated Rainfall

Abstract Using the interior spectral nudging and update cycle (SN+UIC) methods in the regional Weather Research and Forecasting (WRF) Model, the numerical predictions of four persistent severe rainfall (PSR) events during the preflood season in south China were investigated, based on the fact that the global model has an advantage in predicting the large-scale atmospheric variation and the regional model is better in terms of simulating small-scale changes. The simulation results clearly indicated that the SN+UIC improved the prediction of the PSR events’ daily precipitation for moderate, heavy, and torrential rains (10–100 mm day−1). It also improved the simulative forecasts of the two categories of rain with accumulated precipitation above 50 and 100 mm at lead times of 5–11 days. Moreover, the longer the forecast lead time is, the larger the decrease in the Brier score. Additionally, the SN+UIC method decreased the root-mean-square error for accumulated rainfall (6.2%) and relative humidity (5.67%).

scholarly journals A Combined Approach to Improving the Regional Model Forecasts for the Rainy Season in China

2017 ◽  
Vol 145 (11) ◽  
pp. 4593-4603
Author(s):  
Yanfeng Zhao ◽  
Donghai Wang ◽  
Jianjun Xu
Keyword(s):  
Rainy Season ◽  
Large Scale ◽  
Initial Conditions ◽  
Wrf Model ◽  
Regional Model ◽  
Weather Research And Forecasting ◽  
Small Scale ◽  
Wind Fields ◽  
Accumulated Rainfall ◽  
Combined Forecasting

A combined forecasting methodology, into which the spectral nudging, lateral boundary filtering, and update initial conditions methods are incorporated, was employed in the regional Weather Research and Forecasting (WRF) Model. The intent was to investigate the potential for improving the prediction capability for the rainy season in China via using as many merits of the global model having better predictability as it does for the large-scale circulation and of the regional model as it does for the small-scale features. The combined methodology was found to be successful in improving the prediction of the regional atmospheric circulation and precipitation. It performed best for the larger magnitude precipitation, the relative humidity above 800 hPa, and wind fields below 300 hPa. Furthermore, the larger the magnitude and the longer the lead time, the more obvious is the improvement in terms of the accumulated rainfall of persistent severe rainfall events.

scholarly journals Differences between downscaling with spectral and grid nudging using WRF

2012 ◽  
Vol 12 (8) ◽  
pp. 3601-3610 ◽  
Author(s):  
P. Liu ◽  
A. P. Tsimpidi ◽  
Y. Hu ◽  
B. Stone ◽  
A. G. Russell ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Dynamical Downscaling ◽  
Global Climate ◽  
Regional Climate ◽  
Wrf Model ◽  
Global Climate Models ◽  
Small Scale ◽  
Data Set ◽  
Spectral Nudging

Abstract. Dynamical downscaling has been extensively used to study regional climate forced by large-scale global climate models. During the downscaling process, however, the simulation of regional climate models (RCMs) tends to drift away from the driving fields. Developing a solution that addresses this issue, by retaining the large scale features (from the large-scale fields) and the small-scale features (from the RCMs) has led to the development of "nudging" techniques. Here, we examine the performance of two nudging techniques, grid and spectral nudging, in the downscaling of NCEP/NCAR data with the Weather Research and Forecasting (WRF) Model. The simulations are compared against the results with North America Regional Reanalysis (NARR) data set at different scales of interest using the concept of similarity. We show that with the appropriate choice of wave numbers, spectral nudging outperforms grid nudging in the capacity of balancing the performance of simulation at the large and small scales.

scholarly journals Impact of Nudging Parameters on Dynamical Downscaling over CORDEX East Asia Phase II Domain: The Case of Summer 2003

2019 ◽  
Vol 58 (12) ◽  
pp. 2755-2771
Author(s):  
Linyun Yang ◽  
Shuyu Wang ◽  
Jianping Tang ◽  
Xiaorui Niu ◽  
Congbin Fu
Keyword(s):  
Relaxation Time ◽  
East Asia ◽  
Large Scale ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Wrf Model ◽  
Precipitation Event ◽  
Weather Research And Forecasting ◽  
Spectral Nudging ◽  
Thermodynamic Variables

AbstractIn this paper, the sensitivity of the Weather Research and Forecasting (WRF) Model to the nudging parameters in simulating July–August (JJA) precipitation was assessed with 16 experiments over the Coordinated Regional Climate Downscaling Experiment East Asia II (CORDEX-EA-II) domain. The effects of various nudging parameters in spectral nudging (referred to as SN) and grid nudging (referred to as AN) experiments are examined, including wavenumbers, relaxation time, nudging levels, and nudging variables for SN and relaxation time and nudging variables for AN. Results showed that the applications of spectral nudging and grid nudging methods in WRF simulations can improve the model’s ability to reproduce the JJA extreme precipitation event and accompanying large-scale fields in 2003. The major findings include 1) spectral nudging is superior to grid nudging in simulating heavy rainfall and low-level circulation, 2) nudging both kinematic and thermodynamic variables is efficient to better simulate the JJA precipitation for both SN and AN simulations, 3) in SN simulations, the options of wavenumbers display stronger impact on JJA precipitation if nudging solely the kinematic variables instead of both kinematic and thermodynamic variables over wet subregions, and 4) the free developed large-scale processes associated with small nudging wavenumbers can diminish the improvement from nudging both kinematic and thermodynamic variables in simulating subseasonal variations of precipitation. Overall, the experiment that adopts spectral nudging of both kinematic and thermodynamic variables, 1-h relaxation time, and four or eight nudging wavenumbers captures the characteristics of summer climate more reasonably.

Neighborhood-Based Verification of Precipitation Forecasts from Convection-Allowing NCAR WRF Model Simulations and the Operational NAM

2010 ◽  
Vol 25 (5) ◽  
pp. 1495-1509 ◽  
Author(s):  
Adam J. Clark ◽  
William A. Gallus ◽  
Morris L. Weisman
Keyword(s):  
Spatial Scale ◽  
Large Scale ◽  
Wrf Model ◽  
Warm Season ◽  
Precipitation Forecast ◽  
Weather Research And Forecasting ◽  
Lead Times ◽  
Central United States ◽  
Before And After ◽  
Grid Points

Abstract Since 2003 the National Center for Atmospheric Research (NCAR) has been running various experimental convection-allowing configurations of the Weather Research and Forecasting Model (WRF) for domains covering a large portion of the central United States during the warm season (April–July). In this study, the skill of 3-hourly accumulated precipitation forecasts from a large sample of these convection-allowing simulations conducted during 2004–05 and 2007–08 is compared to that from operational North American Mesoscale (NAM) model forecasts using a neighborhood-based equitable threat score (ETS). Separate analyses were conducted for simulations run before and after the implementation in 2007 of positive-definite (PD) moisture transport for the NCAR-WRF simulations. The neighborhood-based ETS (denoted 〈ETS〉r) relaxes the criteria for “hits” (i.e., correct forecasts) by considering grid points within a specified radius r. It is shown that 〈ETS〉r is more useful than the traditional ETS because 〈ETS〉r can be used to diagnose differences in precipitation forecast skill between different models as a function of spatial scale, whereas the traditional ETS only considers the spatial scale of the verification grid. It was found that differences in 〈ETS〉r between NCAR-WRF and NAM generally increased with increasing r, with NCAR-WRF having higher scores. Examining time series of 〈ETS〉r for r = 100 and r = 0 km (which simply reduces to the “traditional” ETS), statistically significant differences between NCAR-WRF and NAM were found at many forecast lead times for 〈ETS〉100 but only a few times for 〈ETS〉0. Larger and more statistically significant differences occurred with the 2007–08 cases relative to the 2004–05 cases. Because of differences in model configurations and dominant large-scale weather regimes, a more controlled experiment would have been needed to diagnose the reason for the larger differences that occurred with the 2007–08 cases. Finally, a compositing technique was used to diagnose the differences in the spatial distribution of the forecasts. This technique implied westward displacement errors for NAM model forecasts in both sets of cases and in NCAR-WRF model forecasts for the 2007–08 cases. Generally, the results are encouraging because they imply that advantages in convection-allowing relative to convection-parameterizing simulations noted in recent studies are reflected in an objective neighborhood-based metric.

scholarly journals Differences between downscaling with spectral and grid nudging using WRF

2012 ◽  
Vol 12 (1) ◽  
pp. 1191-1213 ◽  
Author(s):  
P. Liu ◽  
A. P. Tsimpidi ◽  
Y. Hu ◽  
B. Stone ◽  
A. G. Russell ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Dynamical Downscaling ◽  
Global Climate ◽  
Regional Climate ◽  
Wrf Model ◽  
Global Climate Models ◽  
Small Scale ◽  
Data Set ◽  
Spectral Nudging

Abstract. Dynamical downscaling has been extensively used to study regional climate forced by large-scale global climate models. During the downscaling process, however, the simulation of regional climate models (RCMs) tends to drift away from the driving fields. Developing a solution that addresses this issue, by retaining the large scale features (from the large-scale fields) and the small-scale features (from the RCMs) has led to the development of "nudging" techniques. Here, we examine the performance of two nudging techniques, grid and spectral nudging, in the downscaling of NCEP/NCAR data using Weather Research and Forecasting (WRF) Model. The simulations are compared against the results with North America Regional Reanalysis (NARR) data set at different scales of interest. We show that with the appropriate choice of wave numbers, spectral nudging outperforms grid nudging in the capacity of balancing the performance of simulation at the large and small scales.

scholarly journals Relationship between the Track and Structural Evolution of Hurricane Sandy (2012) Using a Regional Ensemble

2018 ◽  
Vol 146 (12) ◽  
pp. 4279-4302 ◽  
Author(s):  
Alex M. Kowaleski ◽  
Jenni L. Evans
Keyword(s):  
Large Scale ◽  
Wrf Model ◽  
Structural Evolution ◽  
Hurricane Sandy ◽  
Weather Research And Forecasting ◽  
Extratropical Transition ◽  
Ensemble Forecasts ◽  
High Predictability ◽  
Regression Mixture ◽  
The Relationship

Abstract An ensemble of 72 Weather Research and Forecasting (WRF) Model simulations is evaluated to examine the relationship between the track of Hurricane Sandy (2012) and its structural evolution. Initial and boundary conditions are obtained from ECMWF and GEFS ensemble forecasts initialized at 0000 UTC 25 October. The 5-day WRF simulations are initialized at 0000 UTC 27 October, 48 h into the global model forecasts. Tracks and cyclone phase space (CPS) paths from the 72 simulations are partitioned into 6 clusters using regression mixture models; results from the 4 most populous track clusters are examined. The four analyzed clusters vary in mean landfall location from southern New Jersey to Maine. Extratropical transition timing is the clearest difference among clusters; more eastward clusters show later Sandy–midlatitude trough interaction, warm seclusion formation, and extratropical transition completion. However, the intercluster variability is much smaller when examined relative to the landfall time of each simulation. In each cluster, a short-lived warm seclusion forms and contracts through landfall while lower-tropospheric potential vorticity concentrates at small radii. Despite the large-scale similarity among the clusters, relevant intercluster differences in landfall-relative extratropical transition are observed. In the easternmost cluster the Sandy–trough interaction is least intense and the warm seclusion decays the most by landfall. In the second most eastward cluster Sandy retains the most intact warm seclusion at landfall because of a slightly later (relative to landfall) and weaker trough interaction compared to the two most westward clusters. Nevertheless, the remarkably similar large-scale evolution of Sandy among the four clusters indicates the high predictability of Sandy’s warm seclusion extratropical transition before landfall.

Convection Initiation Aided by Lake-Breeze Convergence over the Niagara Peninsula

2019 ◽  
Vol 147 (11) ◽  
pp. 3955-3979 ◽  
Author(s):  
Chun-Chih Wang ◽  
Daniel J. Kirshbaum ◽  
David M. L. Sills
Keyword(s):  
Large Scale ◽  
Inversion Layer ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Lake Breeze ◽  
Moist Convection ◽  
Warm Advection ◽  
American Science ◽  
Convection Initiation ◽  
Cloud Tops

Abstract Observations from the 2015 Environment and Climate Change Canada Pan/Parapan American Science Showcase (ECPASS) and real-case, cloud-resolving numerical simulations with the Weather Research and Forecasting (WRF) Model are used to investigate two cases of moist convection forced by lake-breeze convergence over southern Ontario (18 July and 15 August 2015). The two cases shared several characteristics, including high pressure conditions, similar morning soundings, and isolated afternoon convection along a line of lake-breeze convergence between Lakes Erie and Ontario. However, the convection was significantly stronger in the August case, with robustly deeper clouds and larger radar reflectivities than in the July case. Synoptic and mesoscale analyses of these events reveal that the key difference between them was their large-scale forcing. The July event exhibited a combination of strong warm advection and large-scale descent at midlevels (850–650 hPa), which created an inversion layer that capped cloud tops at 4–6 km. The August case exhibited similar features (large-scale descent and warm advection), but these were focused at higher levels (700–400 hPa) and weaker. As a consequence, the convection in the August case was less suppressed at midlevels and ascended deeper (reaching over 8 km). Although the subcloud updraft along the lake-breeze convergence zone was also found to be stronger in the August case, this difference was found to be an effect, rather than a cause, of stronger moist convection within the cloud layer.

scholarly journals What Is the Predictability Limit of Midlatitude Weather?

2019 ◽  
Vol 76 (4) ◽  
pp. 1077-1091 ◽  
Author(s):  
Fuqing Zhang ◽  
Y. Qiang Sun ◽  
Linus Magnusson ◽  
Roberto Buizza ◽  
Shian-Jiann Lin ◽  
...  
Keyword(s):  
Initial Conditions ◽  
Weather Prediction ◽  
Forecast Model ◽  
Small Scale ◽  
Lead Times ◽  
Winter Storms ◽  
Weather Forecasts ◽  
Numerical Weather ◽  
Forecast Lead Time ◽  
Order Of Magnitude

Abstract Understanding the predictability limit of day-to-day weather phenomena such as midlatitude winter storms and summer monsoonal rainstorms is crucial to numerical weather prediction (NWP). This predictability limit is studied using unprecedented high-resolution global models with ensemble experiments of the European Centre for Medium-Range Weather Forecasts (ECMWF; 9-km operational model) and identical-twin experiments of the U.S. Next-Generation Global Prediction System (NGGPS; 3 km). Results suggest that the predictability limit for midlatitude weather may indeed exist and is intrinsic to the underlying dynamical system and instabilities even if the forecast model and the initial conditions are nearly perfect. Currently, a skillful forecast lead time of midlatitude instantaneous weather is around 10 days, which serves as the practical predictability limit. Reducing the current-day initial-condition uncertainty by an order of magnitude extends the deterministic forecast lead times of day-to-day weather by up to 5 days, with much less scope for improving prediction of small-scale phenomena like thunderstorms. Achieving this additional predictability limit can have enormous socioeconomic benefits but requires coordinated efforts by the entire community to design better numerical weather models, to improve observations, and to make better use of observations with advanced data assimilation and computing techniques.

scholarly journals Comparison of Convective Boundary Layer Velocity Spectra Retrieved from Large- Eddy-Simulation and Weather Research and Forecasting Model Data

2014 ◽  
Vol 53 (2) ◽  
pp. 377-394 ◽  
Author(s):  
Jeremy A. Gibbs ◽  
Evgeni Fedorovich
Keyword(s):  
Boundary Layer ◽  
Convective Boundary Layer ◽  
Wrf Model ◽  
Velocity Fields ◽  
Weather Research And Forecasting ◽  
Small Scale ◽  
Convective Boundary ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Velocity Spectra

AbstractAs computing capabilities expand, operational and research environments are moving toward the use of finescale atmospheric numerical models. These models are attractive for users who seek an accurate description of small-scale turbulent motions. One such numerical tool is the Weather Research and Forecasting (WRF) model, which has been extensively used in synoptic-scale and mesoscale studies. As finer-resolution simulations become more desirable, it remains a question whether the model features originally designed for the simulation of larger-scale atmospheric flows will translate to adequate reproductions of small-scale motions. In this study, turbulent flow in the dry atmospheric convective boundary layer (CBL) is simulated using a conventional large-eddy-simulation (LES) code and the WRF model applied in an LES mode. The two simulation configurations use almost identical numerical grids and are initialized with the same idealized vertical profiles of wind velocity, temperature, and moisture. The respective CBL forcings are set equal and held constant. The effects of the CBL wind shear and of the varying grid spacings are investigated. Horizontal slices of velocity fields are analyzed to enable a comparison of CBL flow patterns obtained with each simulation method. Two-dimensional velocity spectra are used to characterize the planar turbulence structure. One-dimensional velocity spectra are also calculated. Results show that the WRF model tends to attribute slightly more energy to larger-scale flow structures as compared with the CBL structures reproduced by the conventional LES. Consequently, the WRF model reproduces relatively less spatial variability of the velocity fields. Spectra from the WRF model also feature narrower inertial spectral subranges and indicate enhanced damping of turbulence on small scales.

scholarly journals Mesoscale Moisture Transport by the Low-Level Jet during the IHOP Field Experiment

2008 ◽  
Vol 136 (10) ◽  
pp. 3781-3795 ◽  
Author(s):  
Edward I. Tollerud ◽  
Fernando Caracena ◽  
Steven E. Koch ◽  
Brian D. Jamison ◽  
R. Michael Hardesty ◽  
...  
Keyword(s):  
Great Plains ◽  
Cross Sections ◽  
Moisture Transport ◽  
Large Scale ◽  
Wrf Model ◽  
The United States ◽  
Small Scale ◽  
Low Level ◽  
Convective Scale ◽  
Low Level Jet

Previous studies of the low-level jet (LLJ) over the central Great Plains of the United States have been unable to determine the role that mesoscale and smaller circulations play in the transport of moisture. To address this issue, two aircraft missions during the International H2O Project (IHOP_2002) were designed to observe closely a well-developed LLJ over the Great Plains (primarily Oklahoma and Kansas) with multiple observation platforms. In addition to standard operational platforms (most important, radiosondes and profilers) to provide the large-scale setting, dropsondes released from the aircraft at 55-km intervals and a pair of onboard lidar instruments—High Resolution Doppler Lidar (HRDL) for wind and differential absorption lidar (DIAL) for moisture—observed the moisture transport in the LLJ at greater resolution. Using these observations, the authors describe the multiscalar structure of the LLJ and then focus attention on the bulk properties and effects of scales of motion by computing moisture fluxes through cross sections that bracket the LLJ. From these computations, the Reynolds averages within the cross sections can be computed. This allow an estimate to be made of the bulk effect of integrated estimates of the contribution of small-scale (mesoscale to convective scale) circulations to the overall transport. The performance of the Weather Research and Forecasting (WRF) Model in forecasting the intensity and evolution of the LLJ for this case is briefly examined.

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