The lightning assimilation (LTA) technique in the Kain–Fritsch convective parameterization in the Weather Research and Forecasting (WRF) model has been updated and applied to continental and ...hemispheric simulations using lightning flash data obtained from the National Lightning Detection Network (NLDN) and the World Wide Lightning Location Network (WWLLN), respectively. The LTA technique uses lightning data to trigger the Kain–Fritsch convective parameterization via realistic temperature and moisture perturbations. The impact of different values for cumulus parameters associated with the Kain–Fritsch scheme on simulations with and without LTA were evaluated for both the continental and the hemispheric simulations. Comparisons to gauge-based rainfall products and near-surface meteorological observations indicated that the LTA improved the model's performance for most variables. The simulated precipitation with LTA, using WWLLN lightning flashes in the hemispheric applications, was significantly improved over the simulations without LTA when compared to precipitation from satellite observations in the equatorial regions. The simulations without LTA showed significant sensitivity to the cumulus parameters (i.e., user-toggled switches) for monthly precipitation that was as large as 40 % during convective seasons for monthly mean daily precipitation. With LTA, the differences in simulated precipitation due to the different cumulus parameters were minimized. The horizontal grid spacing of the modeling domain strongly influenced the LTA technique and the predicted total precipitation, especially in the coarser scales used for the hemispheric simulation. The user-definable cumulus parameters and domain
resolution manifested the complexity of convective process modeling both
with and without LTA. These results revealed sensitivities to domain resolution, geographic heterogeneity, and the source and quality of the
lightning dataset.
Convective rainfall is often a large source of error in retrospective modeling applications. In particular, positive rainfall biases commonly exist during summer months due to overactive convective ...parameterizations. In this study, lightning assimilation was applied in the Kain‐Fritsch (KF) convective scheme to improve retrospective simulations using the Weather Research and Forecasting (WRF) model. The assimilation method has a straightforward approach: force KF deep convection where lightning is observed and, optionally, suppress deep convection where lightning is absent. WRF simulations were made with and without lightning assimilation over the continental United States for July 2012, July 2013, and January 2013. The simulations were evaluated against NCEP stage‐IV precipitation data and MADIS near‐surface meteorological observations. In general, the use of lightning assimilation considerably improves the simulation of summertime rainfall. For example, the July 2012 monthly averaged bias of 6 h accumulated rainfall is reduced from 0.54 to 0.07 mm and the spatial correlation is increased from 0.21 to 0.43 when lightning assimilation is used. Statistical measures of near‐surface meteorological variables also are improved. Consistent improvements also are seen for the July 2013 case. These results suggest that this lightning assimilation technique has the potential to substantially improve simulation of warm‐season rainfall in retrospective WRF applications.
Key Points
Lightning assimilation was applied in the Kain‐Fritsch convective parameterization in WRF
Lightning assimilation considerably improves mean bias, mean absolute error, and spatial correlation of WRF‐simulated warm‐season rainfall
Lightning assimilation improves statistical measures of near‐surface meteorological variables
RATIONALE:Calcium entry through Orai1 channels drives vascular smooth muscle cell migration and neointimal hyperplasia. The channels are activated by the important growth factor platelet-derived ...growth factor (PDGF). Channel activation is suggested to depend on store depletion, which redistributes and clusters stromal interaction molecule 1 (STIM1), which then coclusters and activates Orai1.
OBJECTIVE:To determine the relevance of STIM1 and Orai1 redistribution in PDGF responses.
METHODS AND RESULTS:Vascular smooth muscle cells were cultured from human saphenous vein. STIM1 and Orai1 were tagged with green and red fluorescent proteins to track them in live cells. Under basal conditions, the proteins were mobile but mostly independent of each other. Inhibition of sarco-endoplasmic reticulum calcium ATPase led to store depletion and dramatic redistribution of STIM1 and Orai1 into coclusters. PDGF did not evoke redistribution, even though it caused calcium release and Orai1-mediated calcium entry in the same time period. After chemical blockade of Orai1-mediated calcium entry, however, PDGF caused redistribution. Similarly, mutagenic disruption of calcium flux through Orai1 caused PDGF to evoke redistribution, showing that calcium flux through the wild-type channels had been filling the stores. Acidification of the extracellular medium to pH 6.4 caused inhibition of Orai1-mediated calcium entry and conferred capability for PDGF to evoke complete redistribution and coclustering.
CONCLUSIONS:The data suggest that PDGF has a nonclustering mechanism by which to activate Orai1 channels and maintain calcium stores replete. Redistribution and clustering become important, however, when the endoplasmic reticulum stress signal of store depletion arises, for example when acidosis inhibits Orai1 channels.
Large‐eddy simulations (LES) and observations are often combined to increase our understanding and improve the simulation of deep convection. This study evaluates a nested LES method that uses the ...Weather Research and Forecasting (WRF) model and, specifically, tests whether the nested LES approach is useful for studying deep convection during a real‐world case. The method was applied on 2 September 2013, a day of continental convection that occurred during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign. Mesoscale WRF output (1.35 km grid length) was used to drive a nested LES with 450 m grid spacing, which then drove a 150 m domain. Results reveal that the 450 m nested LES reasonably simulates observed reflectivity distributions and aircraft‐observed in‐cloud vertical velocities during the study period. However, when examining convective updrafts, reducing the grid spacing to 150 m worsened results. We find that the simulated updrafts in the 150 m run become too diluted by entrainment, thereby generating updrafts that are weaker than observed. Lastly, the 450 m simulation is combined with observations to study the processes forcing strong midlevel cloud/updraft edge downdrafts that were observed on 2 September. Results suggest that these strong downdrafts are forced by evaporative cooling due to mixing and by perturbation pressure forces acting to restore mass continuity around neighboring updrafts. We conclude that the WRF nested LES approach, with further development and evaluation, could potentially provide an effective method for studying deep convection in real‐world cases.
Key Points
Nested large‐eddy simulations are performed for deep convection
Nested LES runs reasonably reproduce observed reflectivity distributions and in‐cloud vertical velocities
Observations and nested LES suggest that strong midlevel downdrafts are forced by evaporative cooling and perturbation pressure forces
The Community Multiscale Air Quality (CMAQ) model is a comprehensive multipollutant air quality modeling system developed and maintained by the US Environmental Protection Agency's (EPA) Office of ...Research and Development (ORD). Recently, version 5.1 of the CMAQ model (v5.1) was released to the public, incorporating a large number of science updates and extended capabilities over the previous release version of the model (v5.0.2). These updates include the following: improvements in the meteorological calculations in both CMAQ and the Weather Research and Forecast (WRF) model used to provide meteorological fields to CMAQ, updates to the gas and aerosol chemistry, revisions to the calculations of clouds and photolysis, and improvements to the dry and wet deposition in the model. Sensitivity simulations isolating several of the major updates to the modeling system show that changes to the meteorological calculations result in enhanced afternoon and early evening mixing in the model, periods when the model historically underestimates mixing. This enhanced mixing results in higher ozone (O
) mixing ratios on average due to reduced NO titration, and lower fine particulate matter (PM
) concentrations due to greater dilution of primary pollutants (e.g., elemental and organic carbon). Updates to the clouds and photolysis calculations greatly improve consistency between the WRF and CMAQ models and result in generally higher O
mixing ratios, primarily due to reduced cloudiness and attenuation of photolysis in the model. Updates to the aerosol chemistry result in higher secondary organic aerosol (SOA) concentrations in the summer, thereby reducing summertime PM
bias (PM
is typically underestimated by CMAQ in the summer), while updates to the gas chemistry result in slightly higher O
and PM
on average in January and July. Overall, the seasonal variation in simulated PM
generally improves in CMAQv5.1 (when considering all model updates), as simulated PM
concentrations decrease in the winter (when PM
is generally overestimated by CMAQ) and increase in the summer (when PM
is generally underestimated by CMAQ). Ozone mixing ratios are higher on average with v5.1 vs. v5.0.2, resulting in higher O
mean bias, as O
tends to be overestimated by CMAQ throughout most of the year (especially at locations where the observed O
is low); however, O
correlation is largely improved with v5.1. Sensitivity simulations for several hypothetical emission reduction scenarios show that v5.1 tends to be slightly more responsive to reductions in NO
(NO + NO
), VOC and SO
(SO
+ SO
) emissions than v5.0.2, representing an improvement as previous studies have shown CMAQ to underestimate the observed reduction in O
due to large, widespread reductions in observed emissions.
Large-eddy simulations (LES) and observations are often combined to increase our understanding and improve the simulation of deep convection. This study evaluates a nested LES method that uses the ...Weather Research and Forecasting (WRF) model and, specifically, tests whether the nested LES approach is useful for studying deep convection during a real-world case. The method was applied on 2 September 2013, a day of continental convection that occurred during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC super(4)RS) campaign. Mesoscale WRF output (1.35km grid length) was used to drive a nested LES with 450m grid spacing, which then drove a 150m domain. Results reveal that the 450m nested LES reasonably simulates observed reflectivity distributions and aircraft-observed in-cloud vertical velocities during the study period. However, when examining convective updrafts, reducing the grid spacing to 150m worsened results. We find that the simulated updrafts in the 150m run become too diluted by entrainment, thereby generating updrafts that are weaker than observed. Lastly, the 450m simulation is combined with observations to study the processes forcing strong midlevel cloud/updraft edge downdrafts that were observed on 2 September. Results suggest that these strong downdrafts are forced by evaporative cooling due to mixing and by perturbation pressure forces acting to restore mass continuity around neighboring updrafts. We conclude that the WRF nested LES approach, with further development and evaluation, could potentially provide an effective method for studying deep convection in real-world cases. Key Points * Nested large-eddy simulations are performed for deep convection * Nested LES runs reasonably reproduce observed reflectivity distributions and in-cloud vertical velocities * Observations and nested LES suggest that strong midlevel downdrafts are forced by evaporative cooling and perturbation pressure forces
Abstract Large‐eddy simulations (LES) and observations are often combined to increase our understanding and improve the simulation of deep convection. This study evaluates a nested LES method that ...uses the Weather Research and Forecasting (WRF) model and, specifically, tests whether the nested LES approach is useful for studying deep convection during a real‐world case. The method was applied on 2 September 2013, a day of continental convection that occurred during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC 4 RS) campaign. Mesoscale WRF output (1.35 km grid length) was used to drive a nested LES with 450 m grid spacing, which then drove a 150 m domain. Results reveal that the 450 m nested LES reasonably simulates observed reflectivity distributions and aircraft‐observed in‐cloud vertical velocities during the study period. However, when examining convective updrafts, reducing the grid spacing to 150 m worsened results. We find that the simulated updrafts in the 150 m run become too diluted by entrainment, thereby generating updrafts that are weaker than observed. Lastly, the 450 m simulation is combined with observations to study the processes forcing strong midlevel cloud/updraft edge downdrafts that were observed on 2 September. Results suggest that these strong downdrafts are forced by evaporative cooling due to mixing and by perturbation pressure forces acting to restore mass continuity around neighboring updrafts. We conclude that the WRF nested LES approach, with further development and evaluation, could potentially provide an effective method for studying deep convection in real‐world cases.
Key Points Nested large‐eddy simulations are performed for deep convection Nested LES runs reasonably reproduce observed reflectivity distributions and in‐cloud vertical velocities Observations and nested LES suggest that strong midlevel downdrafts are forced by evaporative cooling and perturbation pressure forces
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