scholarly journals Evaluation of Cumulus and Microphysics Parameterizations in WRF across the Convective Gray Zone

2019 ◽  
Vol 34 (4) ◽  
pp. 1097-1115 ◽  
Author(s):  
Julia Jeworrek ◽  
Gregory West ◽  
Roland Stull
Keyword(s):  
Great Plains ◽  
Wrf Model ◽  
Mesoscale Convective System ◽  
The United States ◽  
Smooth Transition ◽  
Cumulus Parameterization ◽  
Convective System ◽  
Gray Zone ◽  
Cumulus Scheme ◽  
Mesoscale Convective

Abstract This study evaluates the grid-length dependency of the Weather Research and Forecasting (WRF) Model precipitation performance for two cases in the Southern Great Plains of the United States. The aim is to investigate the ability of different cumulus and microphysics parameterization schemes to represent precipitation processes throughout the transition between parameterized and resolved convective scales (e.g., the gray zone). The cases include the following: 1) a mesoscale convective system causing intense local precipitation, and 2) a frontal passage with light but continuous rainfall. The choice of cumulus parameterization appears to be a crucial differentiator in convective development and resulting precipitation patterns in the WRF simulations. Different microphysics schemes produce very similar outcomes, yet some of the more sophisticated schemes have substantially longer run times. This suggests that this additional computational expense does not necessarily provide meaningful forecast improvements, and those looking to run such schemes should perform their own evaluation to determine if this expense is warranted for their application. The best performing cumulus scheme overall for the two cases studies here was the scale-aware Grell–Freitas cumulus scheme. It was able to reproduce a smooth transition from subgrid- (cumulus) to resolved-scale (microphysics) precipitation with increasing resolution. It also produced the smallest errors for the convective event, outperforming the other cumulus schemes in predicting the timing and intensity of the precipitation.

scholarly journals Climatology of Linear Mesoscale Convective System Morphology in the United States based on Random Forests Method

2021 ◽  
pp. 1-52
Author(s):  
Wenjun Cui ◽  
Xiquan Dong ◽  
Baike Xi ◽  
Zhe Feng
Keyword(s):  
United States ◽  
Great Plains ◽  
Warm Season ◽  
Mesoscale Convective System ◽  
Propagation Speed ◽  
Extreme Rainfall ◽  
The United States ◽  
Convective System ◽  
Large Variability ◽  
Mesoscale Convective

AbstractThis study uses machine learning methods, specifically the random forest (RF), on a radar-based mesoscale convective system (MCS) tracking dataset to classify the five types of linear MCS morphology in the contiguous United States during the period 2004-2016. The algorithm is trained using radar- and satellite-derived spatial and morphological parameters, and reanalysis environmental information from 5-yr manually identified nonlinear and five linear MCS modes. The algorithm is then used to automate the classification of linear MCSs over 8 years with high accuracy, providing a systematic, long-term climatology of linear MCSs. Results reveal that nearly 40% of MCSs are classified as linear MCSs, in which half of the linear events belong to the type of system having a leading convective line. The occurrence of linear MCSs shows large annual and seasonal variations. On average, 113 linear MCSs occur annually during the warm season (through March to October), with most of these events clustered from May through August in the central eastern Great Plains. MCS characteristics, including duration, propagation speed, orientation, and system cloud size, have large variability among the different linear modes. The systems having a trailing convective line and the systems having a back-building area of convection typically move more slowly and have higher precipitation rate, and thus have higher potential in producing extreme rainfall and flash flooding. Analysis of the environmental conditions associated with linear MCSs show that the storm-relative flow is of most importance in determining the organization mode of linear MCSs.

scholarly journals Nocturnal Convection Initiation during PECAN 2015

2019 ◽  
Vol 100 (11) ◽  
pp. 2223-2239 ◽  
Author(s):  
Tammy M. Weckwerth ◽  
John Hanesiak ◽  
James W. Wilson ◽  
Stanley B. Trier ◽  
Samuel K. Degelia ◽  
...  
Keyword(s):  
Great Plains ◽  
Current Knowledge ◽  
Wrf Model ◽  
Mesoscale Convective System ◽  
Convective System ◽  
University Of Oklahoma ◽  
Different Types ◽  
Mesoscale Convective ◽  
Convection Initiation ◽  
The University

AbstractNocturnal convection initiation (NCI) is more difficult to anticipate and forecast than daytime convection initiation (CI). A major component of the Plains Elevated Convection at Night (PECAN) field campaign in the U.S. Great Plains was to intensively sample NCI and its near environment. In this article, we summarize NCI types observed during PECAN: 1 June–16 July 2015. These NCI types, classified using PECAN radar composites, are associated with 1) frontal overrunning, 2) the low-level jet (LLJ), 3) a preexisting mesoscale convective system (MCS), 4) a bore or density current, and 5) a nocturnal atmosphere lacking a clearly observed forcing mechanism (pristine). An example and description of each of these different types of PECAN NCI events are presented. The University of Oklahoma real-time 4-km Weather Research and Forecasting (WRF) Model ensemble forecast runs illustrate that the above categories having larger-scale organization (e.g., NCI associated with frontal overrunning and NCI near a preexisting MCS) were better forecasted than pristine. Based on current knowledge and data from PECAN, conceptual models summarizing key environmental features are presented and physical processes underlying the development of each of these different types of NCI events are discussed.

scholarly journals Sensitivity of a Bowing Mesoscale Convective System to Horizontal Grid Spacing in a Convection-Allowing Ensemble

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 384
Author(s):  
John R. Lawson ◽  
William A. Gallus ◽  
Corey K. Potvin
Keyword(s):  
Mesoscale Convective System ◽  
Real Data ◽  
The United States ◽  
Convective System ◽  
Grid Spacing ◽  
Structure Amplitude ◽  
Cold Pools ◽  
Bow Echo ◽  
Mesoscale Convective ◽  
Horizontal Grid

The bow echo, a mesoscale convective system (MCS) responsible for much hail and wind damage across the United States, is associated with poor skill in convection-allowing numerical model forecasts. Given the decrease in convection-allowing grid spacings within many operational forecasting systems, we investigate the effect of finer resolution on the character of bowing-MCS development in a real-data numerical simulation. Two ensembles were generated: one with a single domain of 3-km horizontal grid spacing, and another nesting a 1-km domain with two-way feedback. Ensemble members were generated from their control member with a stochastic kinetic-energy backscatter scheme, with identical initial and lateral-boundary conditions. Results suggest that resolution reduces hindcast skill of this MCS, as measured with an adaptation of the object-based Structure–Amplitude–Location method. The nested 1-km ensemble produces a faster system than in both the 3-km ensemble and observations. The nested 1-km simulation also produced stronger cold pools, which could be enhanced by the increased (fractal) cloud surface area with higher resolution, allowing more entrainment of dry air and hence increased evaporative cooling.

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.

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 Serial Upstream-Propagating Mesoscale Convective System Events over Southeastern South America

2008 ◽  
Vol 136 (8) ◽  
pp. 3087-3105 ◽  
Author(s):  
Vagner Anabor ◽  
David J. Stensrud ◽  
Osvaldo L. L. de Moraes
Keyword(s):  
South America ◽  
Convective Available Potential Energy ◽  
Mesoscale Convective System ◽  
The United States ◽  
Convective System ◽  
Pressure System ◽  
Low Level ◽  
The North ◽  
Synoptic Conditions ◽  
Mesoscale Convective

Abstract Serial mesoscale convective system (MCS) events with lifetimes over 18 h and up to nearly 70 h are routinely observed over southeastern South America from infrared satellite imagery during the spring and summer. These events begin over the southern La Plata River basin, with individual convective systems generally moving eastward with the cloud-layer-mean wind. However, an important and common subset of these serial MCS events shows individual MCSs moving to the east or southeast, yet the region of convective development as a whole shifts upstream to the north or northwest. Analyses of the composite mean environments from 10 of these upstream-propagating serial MCS events using NCEP–NCAR reanalysis data events indicates that the synoptic conditions resemble those found in mesoscale convective complex environments over the United States. The serial MCS events form within an environment of strong low-level warm advection and strong moisture advection between the surface and 700 hPa from the Amazon region southward. One feature that appears to particularly influence the low-level flow pattern at early times is a strong surface anticyclone located just off the coast of Brazil. At upper levels, the MCSs develop on the anticyclonic side of the entrance region to an upper-level jet. Mean soundings show that the atmosphere is moist from the surface to near 500 hPa, with values of convective available potential energy above 1200 J kg−1 at the time of system initiation. System dissipation and continued upstream propagation to the north and northwest occurs in tandem with a surface high pressure system that crosses the Andes Mountains from the west.

scholarly journals Assimilation of Chinese Doppler Radar and Lightning Data Using WRF-GSI: A Case Study of Mesoscale Convective System

2015 ◽  
Vol 2015 ◽  
pp. 1-17 ◽  
Author(s):  
Yi Yang ◽  
Ying Wang ◽  
Kefeng Zhu
Keyword(s):  
Doppler Radar ◽  
Mesoscale Convective System ◽  
Cumulus Parameterization ◽  
Convective System ◽  
Microphysics Scheme ◽  
Precipitation Prediction ◽  
Mesoscale Convective ◽  
Cloud To Ground Lightning ◽  
Grid Points ◽  
Temperature Tendency

The radar-enhanced GSI (version 3.1) system and the WRF-ARW (version 3.4.1) model were modified to assimilate radar/lightning-proxy reflectivity. First, cloud-to-ground lightning data were converted to reflectivity using a simple assumed relationship between flash density and reflectivity. Next, the reflectivity was used in the cloud analysis of GSI to adjust the cloud/hydrometeors and moisture. Additionally, the radar/lightning-proxy reflectivity was simultaneously converted to a 3D temperature tendency. Finally, the model-calculated temperature tendencies from the explicit microphysics scheme, as well as cumulus parameterization at 3D grid points at which the radar temperature tendency is available, were updated in a forward full-physics step of diabatic digital filter initialization in the WRF-ARW. The WRF-GSI system was tested using a mesoscale convective system that occurred on June 5, 2009, and by assimilating Doppler radar and lightning data, respectively. The forecasted reflectivity with assimilation corresponded more closely to the observed reflectivity than that of the parallel experiment without assimilation, particularly during the first 6 h. After assimilation, the short-range precipitation prediction improved, although the precipitation intensity was stronger than the observed one. In addition, the improvements obtained by assimilating lightning data were worse than those from assimilating radar reflectivity over the first 3 h but improved thereafter.

scholarly journals Diurnal Variation of TRMM/LIS Lightning Flash Radiances

2017 ◽  
Vol 98 (7) ◽  
pp. 1453-1470 ◽  
Author(s):  
Themistoklis Chronis ◽  
William J. Koshak
Keyword(s):  
Diurnal Variation ◽  
Mesoscale Convective System ◽  
Tropical Rainfall Measuring Mission ◽  
The United States ◽  
Global Scale ◽  
Diurnal Variations ◽  
Convective System ◽  
Lightning Flash ◽  
Mesoscale Convective ◽  
Imaging Sensor

Abstract This study provides, for the first time, an analysis of the climatological diurnal variations in the lightning flash radiance data product ε from the Tropical Rainfall Measuring Mission Lightning Imaging Sensor (TRMM/LIS). The ε values over 13 years (2002–14), and over a global scale (∼38°S–38°N), reveal novel and remarkably consistent regional and seasonal patterns as a function of the local solar time (LST). In particular, the diurnal variation of ε (over both continental and oceanic regions) is characterized by a monotonic increase from late afternoon (∼2000 LST), attaining a maximum around 0900 LST, followed by a decreasing trend. The continental (oceanic) ε values reach a broader minimum spanning from ∼1500 to 1900 LST (∼1800 to 2000). The relative diurnal amplitude variation in continental ε is about 45%, compared to about 15% for oceanic ε. This study confirms that the results are not affected by diurnal biases associated with instrument detection or other statistical artifacts. Notable agreement is shown between the diurnal variations of ε and the global-scale (∼38°S–38°N) mesoscale convective system areal extent. Comparisons with recently published diurnal variations of cloud-to-ground lightning peak current over the United States also exhibit a marked similarity. Given the novelty of these findings, a few tentative hypotheses about the underlying physical mechanism(s) are discussed.

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