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.

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.

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 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.

Dynamics of the Stratiform Sector of a Tropical Cyclone Rainband

2013 ◽  
Vol 70 (7) ◽  
pp. 1891-1911 ◽  
Author(s):  
Anthony C. Didlake ◽  
Robert A. Houze
Keyword(s):  
Boundary Layer ◽  
Doppler Radar ◽  
Mesoscale Convective System ◽  
Convective System ◽  
Stratiform Region ◽  
Mesoscale Convective ◽  
Upward Transport ◽  
Radial Outflow ◽  
Convective Cells ◽  
Low Entropy

Abstract Airborne Doppler radar documented the stratiform sector of a rainband within the stationary rainband complex of Hurricane Rita. The stratiform rainband sector is a mesoscale feature consisting of nearly uniform precipitation and weak vertical velocities from collapsing convective cells. Upward transport and associated latent heating occur within the stratiform cloud layer in the form of rising radial outflow. Beneath, downward transport is organized into descending radial inflow in response to two regions of latent cooling. In the outer, upper regions of the rainband, sublimational cooling introduces horizontal buoyancy gradients, which produce horizontal vorticity and descending inflow similar to that of the trailing-stratiform region of a mesoscale convective system. Within the zone of heavier stratiform precipitation, melting cooling along the outer rainband edge creates a midlevel horizontal buoyancy gradient across the rainband that drives air farther inward beneath the brightband. The organization of this transport initially is robust but fades downwind as the convection dissipates. The stratiform-induced secondary circulation results in convergence of angular momentum above the boundary layer and broadening of the storm's rotational wind field. At the radial location where inflow suddenly converges, a midlevel tangential jet develops and extends into the downwind end of the rainband complex. This circulation may contribute to ventilation of the eyewall as inflow of low-entropy air continues past the rainband in both the boundary layer and midlevels. Given the expanse of the stratiform rainband region, its thermodynamic and kinematic impacts likely help to modify the structure and intensity of the total vortex.

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.

Sensitivity of high-resolution precipitation to physics parameterization options in WRF over equatorial regions

2020 ◽  
Author(s):  
Martina Messmer ◽  
Santos J. González-Rojí ◽  
Christoph C. Raible ◽  
Thomas F. Stocker
Keyword(s):  
Boundary Layer ◽  
High Resolution ◽  
Planetary Boundary Layer ◽  
Large Scale ◽  
Wrf Model ◽  
Cumulus Parameterization ◽  
Wave Radiation ◽  
Strong Increase ◽  
Simulated Precipitation ◽  
The Impact

<p>Precipitation patterns and climate variability in East Africa and Western South America present high heterogeneity and complexity. This complexity is a result of large-scale and regional controls, such as surrounding oceans, lakes and topography. The combined effect of these controls has implications on precipitation and temperature, and hence, on water availability, biodiversity and ecosystem services. This study focuses on the impact of different physics parameterization in high-resolution experiments performed over equatorial regions with the Weather Research and Forecasting (WRF) model, and how these options affect the representation of precipitation in those regions.</p><p>As expected, weather and climate in equatorial regions are driven by physical processes different to those important in the mid-latitudes. Hence, it is necessary to test the parameterizations available in the WRF model. Several sensitivity simulations are performed over Kenya and Peru nesting the WRF model inside the state-of-the-art ERA5 reanalysis. A cascade of increasing grid resolutions is used in these simulations, reaching the spatial resolutions of 3 and 1 km in the innermost domains, and thus, convection permitting scales. Parameterization options of the planetary boundary layer (PBL), lake model, radiation, cumulus and microphysics schemes are changed, and their sensitivity to precipitation is tested. The year 2008 is simulated for each of the sensitivity simulations. This year is chosen as a good representative of precipitation dynamics and temperature, as it is neither abnormally wet or hot, nor dry or cold over Kenya and Peru. The simulated precipitation driven by the ERA5 reanalysis is compared against station data obtained from the WMO, and over Kenya additionally against observations from the Centre for Training and Integrated Research in ASAL Development (CETRAD).</p><p>Precipitation is strongly underestimated when adopting a typical parameterization setup for the mid-latitudes. However, results indicate that precipitation amounts and also patterns are substantially improved when changing the cumulus and PBL parameterisations. This strong increase in the simulated precipitation is obtained when using the Grell-Freitas ensemble, RRTM and the Yonsei University schemes for cumulus, long-wave radiation and planetary boundary layer, respectively. During some summer months, the accumulated precipitation is improved by up to 100 mm (80 %) compared to mid-latitudes configuration in several regions of the domains (near the Andes in Peru and over the flatlands in Kenya). Additionally, because the 1- and 2-way nesting options show a similar performance with respect to precipitation, the 1-way nesting option is preferred, as it does not overwrite the solutions in the parent domains. Hence, discontinuous solutions related to switching off the cumulus parameterization can be avoided.</p>

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.

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