The PECAN field campaign assembled a rich array of observations from lower-tropospheric profiling systems, mobile radars and mesonets, and aircraft over the Great Plains during June-July 2015 to better understand nocturnal mesoscale convective systems and their relationship with the stable boundary layer, the low-level jet, and atmospheric bores.

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. KeywordsAgronomy, boundary layers, computer simulation, correlation methods, mathematical models, rain, mesoscale convective system (MCS) rainfall, planetary boundary layer, weather research and forecasting (WRF) model, weather forecasting, cloud microphysics, convective system, ensemble forecasting, forecasting method, parameterization ABSTRACTIn 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 H 2 O Project (IHOP) MCS cases. For each case, three diffe...

Radar data during the period 1 April-31 August 2002 were used to classify all convective storms occurring in a 10-state region of the central United States into nine predominant morphologies, and the severe weather reports associated with each morphology were then analyzed. The morphologies included three types of cellular convection (individual cells, clusters of cells, and broken squall lines), five types of linear systems (bow echoes, squall lines with trailing stratiform rain, lines with leading stratiform rain, lines with parallel stratiform rain, and lines with no stratiform rain), and nonlinear systems. Because linear systems with leading and line-parallel stratiform rainfall were relatively rare in the 2002 sample of 925 events, 24 additional cases of these morphologies from 1996 and 1997 identified by Parker and Johnson were included in the sample. All morphologies were found to pose some risk of severe weather, but substantial differences existed between the number and types of severe weather reports and the different morphologies. Normalizing results per event, nonlinear systems produced the fewest reports of hail, and were relatively inactive for all types of severe weather compared to the other morphologies. Linear systems generated large numbers of reports from all categories of severe weather. Among linear systems, the hail and tornado threat was particularly enhanced in systems having leading and line-parallel stratiform rain. Bow echoes were found to produce far more severe wind reports than any other morphology. The flooding threat was largest in broken lines and linear systems having trailing and line-parallel stratiform rain. Cellular storms, despite much smaller areal coverage, also were abundant producers of severe hail and tornadoes, particularly in broken squall lines. All morphologies were found to pose some risk of severe weather, but substantial differences existed between the number and types of severe weather reports and the different morphologies. Normalizing results per event, nonlinear systems produced the fewest reports of hail, and were relatively inactive for all types of severe weather compared to the other morphologies. Linear systems generated large numbers of reports from all categories of severe weather. Among linear systems, the hail and tornado threat was particularly enhanced in systems having leading and line-parallel stratiform rain. Bow echoes were found to produce far more severe wind reports than any other morphology. The flooding threat was largest in broken lines and linear systems having trailing and line-parallel stratiform rain. Cellular storms, despite much smaller areal coverage, also were abundant producers of severe hail and tornadoes, particularly in broken squall lines.

2An experiment is designed to evaluate and compare precipitation forecasts from a 5-member, 4-km grid-spacing (ENS4) and a 15-member, 20-km grid-spacing (ENS20) Weather Research and Forecasting (WRF) model ensemble, which cover a similar domain over the central United States.The ensemble forecasts are initialized at 2100 UTC on 23 different dates and cover forecast lead times up to 33 hours. Previous work has demonstrated that simulations using convection-allowing resolution (CAR; dx ~ 4-km) have a better representation of the spatial and temporal statistical properties of convective precipitation than coarser models using convective parameterizations. In addition, higher resolution should lead to greater ensemble spread as smaller scales of motion are resolved. Thus, CAR ensembles should provide more accurate and reliable probabilistic forecasts than parameterized-convection resolution (PCR) ensembles.Computation of various precipitation skill metrics for probabilistic and deterministic forecasts reveals that ENS4 generally provides more accurate precipitation forecasts than ENS20, with the differences tending to be statistically significant for precipitation thresholds above 0.25 inches at forecast lead times of 9 to 21 hours (0600 -1800 UTC) for all accumulation intervals analyzed (1-, 3-, and 6-hr). In addition, an analysis of rank histograms and statistical consistency reveals that faster error growth in ENS4 eventually leads to more reliable precipitation forecasts in ENS4 than in ENS20. For the cases examined, these results imply that the skill gained by increasing to CAR outweighs the skill lost by decreasing the ensemble size. Thus, when computational capabilities become available, it will be highly desirable to increase the ensemble resolution from PCR to CAR, even if the size of the ensemble has to be reduced.

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The diurnal cycles of rainfall in 5-km grid-spacing convection-resolving and 22-km grid-spacing nonconvection-resolving configurations of the Weather Research and Forecasting (WRF) model are compared to see if significant improvements can be obtained by using fine enough grid spacing to explicitly resolve convection. Diurnally averaged Hovmöller diagrams, spatial correlation coefficients computed in Hovmöller space, equitable threat scores (ETSs), and biases for forecasts conducted from 1 April to 25 July 2005 over a large portion of the central United States are used for the comparisons. A subjective comparison using Hovmöller diagrams of diurnally averaged rainfall show that the diurnal cycle representation in the 5-km configuration is clearly superior to that in the 22-km configuration during forecast hours 24-48. The superiority of the 5-km configuration is validated by much higher spatial correlation coefficients than in the 22-km configuration. During the first 24 forecast hours the 5-km model forecasts appear to be more adversely affected by model "spinup" processes than the 22-km model forecasts, and it is less clear, subjectively, which configuration has the better diurnal cycle representation, although spatial correlation coefficients are slightly higher in the 22-km configuration. ETSs in both configurations have diurnal oscillations with relative maxima occurring in both configurations at forecast hours corresponding to 0000-0300 LST, while biases also have diurnal oscillations with relative maxima (largest errors) in the 22-km (5-km) configuration occurring at forecast hours corresponding to 1200 (1800) LST. At all forecast hours, ETSs from the 22-km configuration are higher than those in the 5-km configuration. This inconsistency with some of the results obtained using the aforementioned spatial correlation coefficients reinforces discussion in past literature that cautions against using "traditional" verification statistics, such as ETS, to compare high-to low-resolution forecasts. ABSTRACTThe diurnal cycles of rainfall in 5-km grid-spacing convection-resolving and 22-km grid-spacing nonconvection-resolving configurations of the Weather Research and Forecasting (WRF) model are compared to see if significant improvements can be obtained by using fine enough grid spacing to explicitly resolve convection. Diurnally averaged Hovmöller diagrams, spatial correlation coefficients computed in Hovmöller space, equitable threat scores (ETSs), and biases for forecasts conducted from 1 April to 25 July 2005 over a large portion of the central United States are used for the comparisons. A subjective comparison using Hovmöller diagrams of diurnally averaged rainfall show that the diurnal cycle representation in the 5-km configuration is clearly superior to that in the 22-km configuration during forecast hours 24-48. The superiority of the 5-km configuration is validated by much higher spatial correlation coefficients than in the 22-km configuration. During the first 24 forecast hours the 5-km model for...

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 hETSir) relaxes the criteria for ''hits'' (i.e., correct forecasts) by considering grid points within a specified radius r. It is shown that hETSir is more useful than the traditional ETS because hETSir 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 hETSir between NCAR-WRF and NAM generally increased with increasing r, with NCAR-WRF having higher scores. Examining time series of hETSir for r 5 100 and r 5 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 hETSi100 but only a few times for hETSi0. 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 convectionallowing relative to convection-parameterizing simulations noted in recent studies are reflected in an objective neighborhood-based metric. 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 hETSi r ) relaxes the criteria for ''hits'' (i.e., correct forecasts) by co...

A versatile workstation version of the NCEP Eta Model is used to simulate three excessive precipitation episodes in the central United States. These events all resulted in damaging flash flooding and include 16-17 June 1996 in the upper Midwest, 17 July 1996 in western Iowa, and 27 May 1997 in Texas. The episodes reflect a wide range of meteorological situations: (i) a warm core cyclone in June 1996 generated a meso-β-scale region of excessive rainfall from echo training in its warm sector while producing excessive overrunning rainfall to the north of its warm front, (ii) a mesoscale convective complex in July 1996 produced excessive rainfall, and (iii) tornadic thunderstorms in May 1997 resulted in small-scale excessive rains. Model sensitivity to horizontal resolution is investigated using a range of horizontal resolutions comparable to those used in operational and quasi-operational forecasting models. Sensitivity tests are also performed using both the Betts-Miller-Janjic convective scheme (operational at NCEP in 1998) and the Kain-Fritsch scheme. Variations in predicted peak precipitation as resolution is refined are found to be highly case dependent, suggesting forecaster interpretation of increasingly higher resolution model quantitative precipitation forecast (QPF) information will not be straightforward. In addition, precipitation forecasts and QPF response to changing resolution are both found to vary significantly with choice of convective parameterization. ABSTRACT A versatile workstation version of the NCEP Eta Model is used to simulate three excessive precipitation episodes in the central United States. These events all resulted in damaging flash flooding and include 16-17 June 1996 in the upper Midwest, 17 July 1996 in western Iowa, and 27 May 1997 in Texas. The episodes reflect a wide range of meteorological situations: (i) a warm core cyclone in June 1996 generated a meso-␤-scale region of excessive rainfall from echo training in its warm sector while producing excessive overrunning rainfall to the north of its warm front, (ii) a mesoscale convective complex in July 1996 produced excessive rainfall, and (iii) tornadic thunderstorms in May 1997 resulted in small-scale excessive rains.Model sensitivity to horizontal resolution is investigated using a range of horizontal resolutions comparable to those used in operational and quasi-operational forecasting models. Sensitivity tests are also performed using both the Betts-Miller-Janjic convective scheme (operational at NCEP in 1998) and the Kain-Fritsch scheme. Variations in predicted peak precipitation as resolution is refined are found to be highly case dependent, suggesting forecaster interpretation of increasingly higher resolution model quantitative precipitation forecast (QPF) information will not be straightforward. In addition, precipitation forecasts and QPF response to changing resolution are both found to vary significantly with choice of convective parameterization.