Influence of Initial Conditions on the WRF–ARW Model QPF Response to Physical Parameterization Changes

2007 ◽  
Vol 22 (3) ◽  
pp. 501-519 ◽  
Author(s):  
Isidora Jankov ◽  
William A. Gallus ◽  
Moti Segal ◽  
Steven E. Koch
Keyword(s):  
Initial Conditions ◽  
Wrf Model ◽  
Warm Season ◽  
Mesoscale Convective System ◽  
Convective System ◽  
Rainfall Forecasting ◽  
Mesoscale Convective ◽  
Arw Model ◽  
Physics Ensemble ◽  
The Impact

Abstract To assist in optimizing a mixed-physics ensemble for warm season mesoscale convective system rainfall forecasting, the impact of various physical schemes as well as their interactions on rainfall when different initializations were used has been investigated. For this purpose, high-resolution Weather Research and Forecasting (WRF) model simulations of eight International H2O Project events were performed. For each case, three different treatments of convection, three different microphysical schemes, and two different planetary boundary layer (PBL) schemes were used. All cases were initialized with both Local Analyses and Prediction System (LAPS) “hot” start analyses and 40-km Eta Model analyses. To evaluate the impacts of the variation of two different physical schemes and their interaction on the simulated rainfall under the two different initial conditions, the factor separation method was used. The sensitivity to the use of various physical schemes and their interactions was found to be dependent on the initialization dataset. Runs initialized with Eta analyses appeared to be influenced by the use of the Betts–Miller–Janjić scheme in that model’s assimilation system, which tended to reduce the WRF’s sensitivity to changes in the microphysical scheme compared with that present when LAPS analyses were used for initialization. In addition, differences in initialized thermodynamics resulted in changes in sensitivity to PBL and convective schemes. With both initialization datasets, the greatest sensitivity to the simulated rain rate was due to changes in the convective scheme. However, for rain volume, substantial sensitivity was present due to changes in both the physical parameterizations and the initial datasets.

scholarly journals The Impact of Different WRF Model Physical Parameterizations and Their Interactions on Warm Season MCS Rainfall

2005 ◽  
Vol 20 (6) ◽  
pp. 1048-1060 ◽  
Author(s):  
Isidora Jankov ◽  
William A. Gallus ◽  
Moti Segal ◽  
Brent Shaw ◽  
Steven E. Koch
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Wrf Model ◽  
Warm Season ◽  
Mesoscale Convective System ◽  
Skill Score ◽  
Convective System ◽  
Mesoscale Convective ◽  
Physics Ensemble ◽  
The Impact

Abstract In recent years, a mixed-physics ensemble approach has been investigated as a method to better predict mesoscale convective system (MCS) rainfall. For both mixed-physics ensemble design and interpretation, knowledge of the general impact of various physical schemes and their interactions on warm season MCS rainfall forecasts would be useful. Adopting the newly emerging Weather Research and Forecasting (WRF) model for this purpose would further emphasize such benefits. To pursue this goal, a matrix of 18 WRF model configurations, created using different physical scheme combinations, was run with 12-km grid spacing for eight International H2O Project (IHOP) MCS cases. For each case, three different treatments of convection, three different microphysical schemes, and two different planetary boundary layer schemes were used. Sensitivity to physics changes was determined using the correspondence ratio and the squared correlation coefficient. The factor separation method was also used to quantify in detail the impacts of the variation of two different physical schemes and their interaction on the simulated rainfall. Skill score measures averaged over all eight cases for all 18 configurations indicated that no one configuration was obviously best at all times and thresholds. The greatest variability in forecasts was found to come from changes in the choice of convective scheme, although notable impacts also occurred from changes in the microphysics and planetary boundary layer (PBL) schemes. Specifically, changes in convective treatment notably impacted the forecast of system average rain rate, while forecasts of total domain rain volume were influenced by choices of microphysics and convective treatment. The impact of interactions (synergy) of different physical schemes, although occasionally of comparable magnitude to the impacts from changing one scheme alone (compared to a control run), varied greatly among cases and over time, and was typically not statistically significant.

scholarly journals Diagnosing Convective Dependencies on Near-Storm Environments Using Ensemble Sensitivity Analyses

2019 ◽  
Vol 147 (2) ◽  
pp. 495-517 ◽  
Author(s):  
Christopher A. Kerr ◽  
David J. Stensrud ◽  
Xuguang Wang
Keyword(s):  
Wind Shear ◽  
Initial Conditions ◽  
Wrf Model ◽  
Vertical Wind Shear ◽  
Mesoscale Convective System ◽  
Vertical Wind ◽  
Sensitivity Analyses ◽  
Convective System ◽  
Mesoscale Convective ◽  
Storm Evolution

AbstractConvection intensity and longevity is highly dependent on the surrounding environment. Ensemble sensitivity analysis (ESA), which quantitatively and qualitatively interprets impacts of initial conditions on forecasts, is applied to very short-term (1–2 h) convective-scale forecasts for three cases during the Mesoscale Predictability Experiment (MPEX) in 2013. The ESA technique reveals several dependencies of individual convective storm evolution on their nearby environments. The three MPEX cases are simulated using a previously verified 36-member convection-allowing model (Δx = 3 km) ensemble created via the Weather Research and Forecasting (WRF) Model. Radar and other conventional observations are assimilated using an ensemble adjustment Kalman filter. The three cases include a mesoscale convective system (MCS) and both nontornadic and tornadic supercells. Of the many ESAs applied in this study, one of the most notable is the positive sensitivity of supercell updraft helicity to increases in both storm inflow region deep and shallow vertical wind shear. This result suggests that larger values of vertical wind shear within the storm inflow yield higher values of storm updraft helicity. Results further show that the supercell storms quickly enhance the environmental vertical wind shear within the storm inflow region. Application of ESA shows that these storm-induced perturbations then affect further storm evolution, suggesting the presence of storm–environment feedback cycles where perturbations affect future mesocyclone strength. Overall, ESA can provide insight into convection dependencies on the near-storm environment.

Multiscale Characteristics and Evolution of Perturbations for Warm Season Convection-Allowing Precipitation Forecasts: Dependence on Background Flow and Method of Perturbation

2014 ◽  
Vol 142 (3) ◽  
pp. 1053-1073 ◽  
Author(s):  
Aaron Johnson ◽  
Xuguang Wang ◽  
Ming Xue ◽  
Fanyou Kong ◽  
Gang Zhao ◽  
...  
Keyword(s):  
Warm Season ◽  
Mesoscale Convective System ◽  
Haar Wavelet ◽  
Precipitation Forecast ◽  
Initial Time ◽  
Small Scale ◽  
Convective System ◽  
Mesoscale Convective ◽  
Perturbation Energy ◽  
The Impact

Abstract Multiscale convection-allowing precipitation forecast perturbations are examined for two forecasts and systematically over 34 forecasts out to 30-h lead time using Haar Wavelet decomposition. Two small-scale initial condition (IC) perturbation methods are compared to the larger-scale IC and physics perturbations in an experimental convection-allowing ensemble. For a precipitation forecast driven primarily by a synoptic-scale baroclinic disturbance, small-scale IC perturbations resulted in little precipitation forecast perturbation energy on medium and large scales, compared to larger-scale IC and physics (LGPH) perturbations after the first few forecast hours. However, for a case where forecast convection at the initial time grew upscale into a mesoscale convective system (MCS), small-scale IC and LGPH perturbations resulted in similar forecast perturbation energy on all scales after about 12 h. Small-scale IC perturbations added to LGPH increased total forecast perturbation energy for this case. Averaged over 34 forecasts, the small-scale IC perturbations had little impact on large forecast scales while LGPH accounted for about half of the error energy on such scales. The impact of small-scale IC perturbations was also less than, but comparable to, the impact of LGPH perturbations on medium scales. On small scales, the impact of small-scale IC perturbations was at least as large as the LGPH perturbations. The spatial structure of small-scale IC perturbations affected the evolution of forecast perturbations, especially at medium scales. There was little systematic impact of the small-scale IC perturbations when added to LGPH. These results motivate further studies on properly sampling multiscale IC errors.

scholarly journals The Impact of Low-Level Moisture Errors on Model Forecasts of an MCS Observed during PECAN

2017 ◽  
Vol 145 (9) ◽  
pp. 3599-3624 ◽  
Author(s):  
John M. Peters ◽  
Erik R. Nielsen ◽  
Matthew D. Parker ◽  
Stacey M. Hitchcock ◽  
Russ S. Schumacher
Keyword(s):  
Convective Available Potential Energy ◽  
Mesoscale Convective System ◽  
Squall Line ◽  
Convective System ◽  
Low Level ◽  
Eastern Flank ◽  
Western Flank ◽  
Mesoscale Convective ◽  
Outflow Boundary ◽  
The Impact

This article investigates errors in forecasts of the environment near an elevated mesoscale convective system (MCS) in Iowa on 24–25 June 2015 during the Plains Elevated Convection at Night (PECAN) field campaign. The eastern flank of this MCS produced an outflow boundary (OFB) and moved southeastward along this OFB as a squall line. The western flank of the MCS remained quasi stationary approximately 100 km north of the system’s OFB and produced localized flooding. A total of 16 radiosondes were launched near the MCS’s eastern flank and 4 were launched near the MCS’s western flank. Convective available potential energy (CAPE) increased and convective inhibition (CIN) decreased substantially in observations during the 4 h prior to the arrival of the squall line. In contrast, the model analyses and forecasts substantially underpredicted CAPE and overpredicted CIN owing to their underrepresentation of moisture. Numerical simulations that placed the MCS at varying distances too far to the northeast were analyzed. MCS displacement error was strongly correlated with models’ underrepresentation of low-level moisture and their associated overrepresentation of the vertical distance between a parcel’s initial height and its level of free convection ([Formula: see text], which is correlated with CIN). The overpredicted [Formula: see text] in models resulted in air parcels requiring unrealistically far northeastward travel in a region of gradual meso- α-scale lift before these parcels initiated convection. These results suggest that erroneous MCS predictions by NWP models may sometimes result from poorly analyzed low-level moisture fields.

scholarly journals Synoptic Control of Heavy-Rain-Producing Convective Training Episodes

2014 ◽  
Vol 142 (7) ◽  
pp. 2464-2482 ◽  
Author(s):  
John M. Peters ◽  
Paul J. Roebber
Keyword(s):  
Initial Conditions ◽  
Mesoscale Convective System ◽  
Heavy Rain ◽  
Convective System ◽  
Lateral Boundary ◽  
Synoptic Scale ◽  
Model Simulations ◽  
Scale Uncertainty ◽  
Lateral Boundary Conditions ◽  
Mesoscale Convective

Abstract This study examines the degree to which the downscale cascade of information from synoptic-scale motions constrains error growth in simulations of a particular type of heavy-rain-producing mesoscale convective system known as training lines. A total of 21 cases of training convection over a 7-yr period from 2000 to 2006 that produced extreme rainfall were dynamically downscaled from reanalysis data using a high-resolution convection-permitting configuration of the Weather Research and Forecasting Model. The NCEP/Department of Energy (DOE)-II and Interim ECMWF Re-Analysis (ERA-Interim), representing lower- and higher-resolution datasets, respectively, were used for this purpose. In most cases the model simulations were able to reproduce qualitative aspects of observed storm structure, including subjectively classified mesoscale convective system archetype and training characteristics, despite the absence of mesoscale features in the reanalysis datasets used to provide initial conditions and lateral boundary conditions to the simulations. Furthermore, models were capable of predicting that a heavy-precipitation event would occur in nearly every case. Increasing the horizontal resolution of the reanalysis dataset used for initial conditions and lateral boundary conditions did not result in measurable improvement in simulated precipitation placement skill relative to observations. A quantitative relationship between a measure of synoptic-scale uncertainty in the atmospheric state and error in the model forecast accumulated precipitation was established, with larger synoptic-scale uncertainty tending to be associated with larger model error. This result suggests that synoptic-scale uncertainty in numerical weather prediction model simulations partially controls error in the placement of heavy convective precipitation.

Does Increased Predicted Warm-Season Rainfall Indicate Enhanced Likelihood of Rain Occurrence?

10.1175/820.1 ◽  
2004 ◽  
Vol 19 (6) ◽  
pp. 1127-1135 ◽  
Author(s):  
William A. Gallus ◽  
Moti Segal
Keyword(s):  
Wrf Model ◽  
Warm Season ◽  
Mesoscale Convective System ◽  
The United States ◽  
Precipitation Forecast ◽  
Convective System ◽  
Good Reliability ◽  
Relative Operating Characteristic ◽  
Probabilistic Forecasts ◽  
Test Sets

Abstract The likelihood of simulated rainfall above a specified threshold being observed is evaluated as a function of the amounts predicted by two mesoscale models. Evaluations are performed for 20 warm-season mesoscale convective system events over the upper Midwest of the United States. Simulations were performed using 10-km versions of the National Centers for Environmental Prediction Eta Model and the Weather Research and Forecasting (WRF) model, with two different convective parameterizations tested in both models. It was found that, despite large differences in the biases of these different models and configurations, a robust relationship was present whereby a substantial increase in the likelihood of observed rainfall exceeding a specified threshold occurred in areas where the model runs forecast higher rainfall amounts. Rainfall was found to be less likely to occur in those areas where the models indicated no rainfall than it was elsewhere in the domain; it was more likely to occur in those regions where rainfall was predicted, especially where the predicted rainfall amounts were largest. The probability of rainfall relative-operating-characteristic and relative-operating-level curves showed that probabilistic forecasts determined from quantitative precipitation forecast values had skill comparable to the skill obtained using more traditional methods in which probabilities are based on the fraction of ensemble members experiencing rainfall. When the entire sample of cases was broken into training and test sets, the probability forecasts of the test sets evidenced good reliability. The relationship noted should provide some additional guidelines to operational forecasters. The results imply that the tested models are better able to indicate the regions where atmospheric processes are most favorable for convective rainfall (where the models generate enhanced amounts) than they are able to predict accurately the rainfall amounts that will be observed.

scholarly journals Increase of the aerosol hygroscopicity by cloud processing in a mesoscale convective system: a case study from the AMMA campaign

2008 ◽  
Vol 8 (23) ◽  
pp. 6907-6924 ◽  
Author(s):  
S. Crumeyrolle ◽  
L. Gomes ◽  
P. Tulet ◽  
A. Matsuki ◽  
A. Schwarzenboeck ◽  
...  
Keyword(s):  
Cloud Condensation Nuclei ◽  
Mesoscale Convective System ◽  
Atmospheric Model ◽  
Dust Particles ◽  
Convective System ◽  
Cloud Processing ◽  
Before And After ◽  
Mesoscale Convective ◽  
The Impact ◽  
Aerosol Properties

Abstract. Aerosol properties were measured during an airborne campaign experiment that took place in July 2006 in West Africa within the framework of the African Monsoon Multidisciplinary Analyses (AMMA). The goal of the present study was to determine the main microphysical processes that affect the aerosols during the passage of a mesoscale convective system (MCS) over the region of Niamey in Niger. A significant change in the aerosol profiles measured before and after the passage of the MCS was found in a layer located between 1300 and 3000 m, where the aerosol concentration drastically decreased after the passage of the MCS. Concurrently, a significant increase in the cloud condensation nuclei (CCN) fraction was also observed during the post-MCS period in the same layer. Moreover, the results of the elemental composition analyses of individual particles collected in this layer after the MCS passage have shown higher contributions of sulfate, nitrate and chloride to the total aerosol mass. A mesoscale atmospheric model with on-line dust parameterization and Lagrangian backtrajectories was used to interpret the impact of the MCS on the aerosol properties. The results of the simulation show that the MCS 1) generates dust particles at the surface in the gust front of the system and washout of particles during the system precipitation, 2) modifies the aerosol mixing state (intensive aerosol property) through cloud processing, and 3) enhances CCN activity of particles through coating by soluble material.

scholarly journals Impacts of Dust–Radiation versus Dust–Cloud Interactions on the Development of a Modeled Mesoscale Convective System over North Africa

2019 ◽  
Vol 147 (9) ◽  
pp. 3301-3326 ◽  
Author(s):  
Chu-Chun Huang ◽  
Shu-Hua Chen ◽  
Yi-Chiu Lin ◽  
Kenneth Earl ◽  
Toshihisa Matsui ◽  
...  
Keyword(s):  
North Africa ◽  
Dust Cloud ◽  
Mesoscale Convective System ◽  
Model Verification ◽  
Convective System ◽  
Mesoscale Convective ◽  
Cloud Development ◽  
Radiation Induced ◽  
Cloud Effect ◽  
The Impact

AbstractThis study evaluates the impact of dust–radiation–cloud interactions on the development of a mesoscale convective system (MCS) by comparing numerical experiments run with and without dust–radiation and/or dust–cloud interactions. An MCS that developed over North Africa on 4–6 July 2010 is used as a case study. The CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellites passed over the center of the MCS after it reached maturity, providing valuable profiles of aerosol backscatter and cloud information for model verification. The model best reproduces the MCS’s observed cloud structure and morphology when both dust–radiation and dust–cloud interactions are included. Our results indicate that the dust–radiation effect has a far greater influence on the MCS’s development than the dust-cloud effect. Results show that the dust-radiative effect, both with and without the dust–cloud interaction, briefly delays the MCS’s formation but ultimately produces a stronger storm with a more extensive anvil cloud. This is caused by dust–radiation-induced changes to the MCS’s environment. The impact of the dust–cloud effect on the MCS, on the other hand, is greatly affected by the presence of the dust–radiation interaction. The dust–cloud effect alone slows initial cloud development but enhances heterogeneous ice nucleation and extends cloud lifetime. When the dust–radiation interaction is added, increased transport of dust into the upper portions of the storm—due to a dust–radiation-driven increase in convective intensity—allows dust–cloud processes to more significantly enhance heterogeneous freezing activity earlier in the storm’s development, increasing updraft strength, hydrometeor growth (particularly for ice particles), and rainfall.

scholarly journals Influences of Horizontal Grid Spacing and Microphysics on WRF Forecasts of Convective Morphology Evolution for Nocturnal MCSs in Weakly Forced Environments

2019 ◽  
Vol 34 (5) ◽  
pp. 1495-1517 ◽  
Author(s):  
Jonathan E. Thielen ◽  
William A. Gallus
Keyword(s):  
Wrf Model ◽  
Forecast Accuracy ◽  
Warm Season ◽  
Grid Spacing ◽  
Convective Systems ◽  
Model Configuration ◽  
Mesoscale Convective ◽  
Microphysical Parameterization ◽  
The Impact ◽  
Horizontal Grid

Abstract Nocturnal mesoscale convective systems (MCSs) are important phenomena because of their contributions to warm-season precipitation and association with severe hazards. Past studies have shown that their morphology remains poorly forecast in current convection-allowing models operating at 3–4-km horizontal grid spacing. A total of 10 MCS cases occurring in weakly forced environments were simulated using the Weather Research and Forecasting (WRF) Model at 3- and 1-km horizontal grid spacings to investigate the impact of increased resolution on forecasts of convective morphology and its evolution. These simulations were conducted using four microphysics schemes to account for additional sensitivities to the microphysical parameterization. The observed and corresponding simulated systems were manually classified into detailed cellular and linear modes, and the overall morphology depiction and the forecast accuracy of each model configuration were evaluated. In agreement with past studies, WRF was found to underpredict the occurrence of linear modes and overpredict cellular modes at 3-km horizontal grid spacing with all microphysics schemes tested. When grid spacing was reduced to 1 km, the proportion of linear systems increased. However, the increase was insufficient to match observations throughout the evolution of the systems, and the accuracy scores showed no statistically significant improvement. This suggests that the additional linear modes may have occurred in the wrong subtypes, wrong systems, and/or at the wrong times. Accuracy scores were also shown to decrease with forecast length, with the primary decrease in score generally occurring during upscale growth in the early nocturnal period.

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