Convective Parameterization Schemes Research Articles

Parameter Modulation of Madden-Julian Oscillation Behaviors in BCC_CSM1.2: The Key Role of Moisture-Shallow Convection Feedback

To reveal key parameter-related physical mechanisms in simulating Madden-Julian Oscillation (MJO), seven physical parameters in the convection and cloud parameterization schemes of Beijing Climate Center Climate System Model (BCC_CSM1.2) are perturbed with Latin hypercube sampling method. A new strategy is proposed to select runs with good and poor MJO simulations among 85 generated ones. Outputs and parameter values from good and poor simulations are composited separately for comparison. Among the seven chosen parameters, a decreased value of precipitation efficiency for shallow convection, higher values of relative humidity threshold for low stable clouds and evaporation efficiency for deep convective precipitation are crucial to simulate a better MJO. Changes of the three parameters act together to suppress heavy precipitation and increase the frequency of light rainfall over the Indo-Pacific region, supplying more moisture in low and middle troposphere. As a result of a wetter lower troposphere ahead of the MJO main convection, the low-level moisture preconditioning along with the leading shallow convection tends to be enhanced, favorable for MJO’s further development and eastward propagation. The MJO’s further propagation across the Maritime Continent (MC) in good simulations is accompanied with more land precipitation dominated by shallow convection. Therefore, the above-mentioned three parameters are found to be crucial parameters out of the seven ones for MJO simulation, providing an inspiration for better MJO simulation and prediction with this model. This work is valuable as it highlights the key role of moisture-shallow convection feedback in the MJO dynamics.

Assessing the performance evaluation of different convective parameterization schemes in simulating the intensity of severe cyclonic storms over the Bay of Bengal region

In the present work, the performance of six convective parameterization schemes (CPSs) of the Weather Research and Forecasting model is tested for the intensity simulation of the cyclonic storms Mala, Sidr, Nargis, Aila, Laila, Jal and Thane which formed over the Bay of Bengal, with a special focus on Jal (formed in November 2010). It is found that the Grell‐3, new Kain–Fritsch and old simplified Arakawa–Schubert CPSs provide higher intensity and give higher divergence in the upper‐level convective precipitation rate, horizontal eddy viscosity, eddy viscosity of heat and total advective moisture tendency than other tested CPSs. It is noted that no single CPS can be assumed “best” for simulating all characteristics of a storm including intensity, track, rainfall amount, the spatial distribution of rainfall, and landfall (time and location). The study also incorporated some of the critically simulated parameters such as vorticity (shear, curvature and total), latent heating, relative humidity, equivalent potential temperature, cloud water content and cloud fraction in the intensity forecast and their importance in the cyclone forecast is discussed. The CPSs influence the forecasted convective precipitation rate of the storm and have a good correlation with the maximum surface wind, cloud fraction and upper‐level divergence.

The Interaction Between Boundary Layer and Convection Schemes in a WRF Simulation of Post Cold Frontal Clouds Over the ARM East North Atlantic Site

AbstractThe correct representation of low‐level midlatitude clouds found in the wake of cold fronts strongly relies on the representation of planetary boundary layer (PBL) and convection processes, which are typically parameterized separately in numerical models. Using the Weather Research and Forecasting Model (WRF), this study investigates how distinct pairs of PBL and convection parameterization schemes represent cloud fraction in the post cold frontal region. The simulations focus on the region of the Department of Energy Atmospheric Radiation Measurement (ARM) Eastern North Atlantic observation site in the Azores Islands in the wake of a cold front that passed on 25 December 2015. Different PBL and convection schemes are combined to create 12 distinct configurations. The main differences between the selected physical parameterizations are the strength of vertical mixing and the entrainment. The simulations produce a wide range of cloud fractions, where some configurations significantly underestimate while others clearly overestimate satellite and surface‐based estimates of cloud fraction. A skill score is used to quantitatively assess the performance of each configuration with respect to ground‐based radar data. The key processes that are found to significantly impact the cloud fraction distribution are the strength of the PBL decoupling, the vertical wind shear, entrainment and detrainment rates in shallow convection, and the occurrence of drizzle. This indicates that to successfully simulate post cold frontal clouds, modeled physics must balance strong internal vertical mixing and weak exchange with the free troposphere. For this case study, cloud fraction was more sensitive to the choice of convection scheme than PBL scheme.

Seasonal Climate Forecast For The Alcântara Launch Center - Brazil

This work analyzed the performance of three cumulus convection parameterization schemes (Kain-Fritsch, Emanuel and Grell/Emanuel) in forecasting the seasonal climate during the transition from rainy to dry period (June to July 2017) in Alcântara Launch Center (ALC) located in Maranhão State-Brazil. For this reason, the outputs from the global NCEP climate forecast system (CFSv2) were used as initial and boundary conditions in the Regional Climate Model (RegCM4.4). The results also focused on the vertical wind profile in the lower atmosphere in the ALC. The forecasts of this variable were validated with data from the wind profile registered by a micrometeorological tower in ALC. The forecasts had better skill in represent the intensity wind in June/July on average and the better convective scheme was Grell Convection Scheme (the Land)/Emanuel convection Scheme (the Ocean).

Why Does Deep Convection Have Different Sensitivities to Temperature Perturbations in the Lower versus Upper Troposphere?

Abstract Previous studies have documented that deep convection responds more strongly to above-the-cloud-base temperature perturbations in the lower troposphere than to those in the upper troposphere, a behavior that is important to the dynamics of large-scale moist flows, such as convectively coupled waves. A number of factors may contribute to this differing sensitivity, including differences in buoyancy, vertical velocity, and/or liquid water content in cloud updrafts in the lower versus upper troposphere. Quantifying the contributions from these factors can help to guide the development of convective parameterization schemes. We tackle this issue by tracking Lagrangian particles embedded in cloud-resolving simulations within a linear response framework. The results show that both the differences in updraft buoyancy and vertical velocity play a significant role, with the vertical velocity being the more important, and the effect of liquid water content is only secondary compared to the other two factors. These results indicate that cloud updraft vertical velocities need to be correctly modeled in convective parameterization schemes in order to properly account for the differing convective sensitivities to temperature perturbations at different heights of the free troposphere.

HWRF Based Ensemble Prediction System Using Perturbations from GEFS and Stochastic Convective Trigger Function

ABSTRACT In this study, an ensemble prediction system (EPS) for the operational Hurricane Weather Research and Forecast (HWRF) model at the Environmental Modeling Center (EMC) of National Centers for Environmental Prediction (NCEP) is introduced and evaluated. The HWRF-EPS takes into account two main sources of uncertainties related to the initial/boundary conditions and the model physics by 1) using the large scale fields from NCEP Global Ensemble Forecast System (GEFS); and 2) stochastically perturbing the convective trigger function in the cumulus convection parameterization scheme. Verification for the 2011-2012 North Atlantic hurricane seasons shows that HWRF-EPS outperforms its deterministic versions at all lead times for both track and intensity forecast errors. Statistical characteristics are investigated and analyzed to demonstrate the effectiveness and robustness of the HWRF-EPS. The relationship between ensemble spread and forecast error for track and intensity in the HWRF-EPS indicated that the spread is likely more useful as a predictor of forecast error when it has moderately low values. Rank histogram analysis shows that the HWRF-EPS is well dispersed in both track and intensity forecasts except for the systematic errors inherited from the deterministic version. Further comparison with 2012 hurricane season’s top-flight models shows improved track and intensity forecasts from the HWRF-EPS.

Improving Seasonal Prediction of East Asian Summer Rainfall Using NESM3.0: Preliminary Results

It has been an outstanding challenge for global climate models to simulate and predict East Asia summer monsoon (EASM) rainfall. This study evaluated the dynamical hindcast skills with the newly developed Nanjing University of Information Science and Technology Earth System Model version 3.0 (NESM3.0). To improve the poor prediction of an earlier version of NESM3.0, we modified convective parameterization schemes to suppress excessive deep convection and enhance insufficient shallow and stratiform clouds. The new version of NESM3.0 with modified parameterizations (MOD hereafter) yields improved rainfall prediction in the northern and southern China but not over the Yangtze River Valley. The improved prediction is primarily attributed to the improvements in the predicted climatological summer mean rainfall and circulations, Nino 3.4 SST anomaly, and the rainfall anomalies associated with the development and decay of El Nino events. However, the MOD still has biases in the predicted leading mode of interannual variability of precipitation. The leading mode captures the dry (wet) anomalies over the South China Sea (northern East Asia) but misplaces precipitation anomalies over the Yangtze River Valley. The model can capture the interannual variation of the circulation indices very well. The results here suggest that, over East Asia land regions, the skillful rainfall prediction relies on not only model’s capability in predicting better summer mean and ENSO teleconnection with EASM, but also accurate prediction of the leading modes of interannual variability.

Assessment of convective parametrization schemes over the Indian subcontinent using a regional climate model

An effort is made to investigate the performance of convective parameterization schemes on the simulation of characteristic features of monsoon rainfall over the Indian subcontinent using a regional climate model (RegCM). The sensitivity experiments with seven different convective parameterization schemes (CPSs) are carried out for this purpose. The simulated precipitation, temperature and wind fields are compared against the available observations and reanalysis dataset. The sensitivity experiments using “Grell” and “Massachusetts Institute of Technology over land and Grell over ocean (MLGO)” CPS show better performance in the simulation of precipitation, near-surface air temperature and circulation pattern over India as compared to the experiments using other CPSs. A systematic dry bias is seen in the simulations of summer monsoon rainfall in all the experiments, but the magnitude of the bias is lowest in the MLGO experiment. The Grell and MLGO experiments also show better performance in the simulation of seasonal cycle of summer monsoon rainfall. The relative performance of CPSs in simulating the vertical structure of temperature anomaly, relative vorticity anomaly and divergence anomaly associated with the summer monsoon rainfall over the Central Indian region is also investigated.

Consistency between the cloud and radiation processes in a numerical forecasting model

In this study, the radiation process in the Korean Integrated Model (KIM) is modified to calculate the cloud radiative forcing keeping a physical consistency with the microphysics, convection, and cloudiness schemes in an aspect of hydrometeor. A formula to calculate effective radii of cloud water in radiation scheme of the KIM is modified to be consistent with that in the microphysics scheme and the radiative effect of a subgrid-scale hydrometeor is considered along with convective parameterization and cloudiness schemes. The impacts of these modifications on radiation and precipitation are diagnosed via an observation comparison, and a detailed analysis of these impacts is conducted. Especially, the contrasting feedback of the subgrid-scale hydrometeor on precipitation over the land and the ocean is separately discussed.

A Climatological Study of Western Mediterranean Medicanes in Numerical Simulations with Explicit and Parameterized Convection

The semi-enclosed Mediterranean basin, surrounded by high mountains, is placed in a favorable location for cyclonic storms development. Most of these are extratropical cyclones of baroclinic and orographic origin, but occasionally, some low pressure systems may develop to assume features characteristic of tropical cyclones. Medicanes (MEDIterranean hurriCANES) are infrequent and small-sized tropical-like cyclones. They originate and develop over sea, and are associated with strong winds and heavy precipitations. Proper definitions and classifications for Medicanes are still partially lacking, and systematic climatic studies have appeared only in recent years. In this work, we provide climatologies of Medicanes in the Western Mediterranean basin based on multidecadal runs performed with the Weather Research and Forecasting regional model with different resolutions and setups. The detection of Medicanes is based on a cyclone tracking algorithm and on the methodology of Hart cyclone phase space diagrams. We compare the statistics of Medicanes in the historical period 1979–1998 between runs at a resolution of 11 km with different convective parameterizations and microphysics schemes and one run at a resolution of 4 km with explicitly resolved convection. We show how different convective parameterization schemes lead to different statistics of Medicanes, while the use of different microphysical schemes impacts the length of the cyclone trajectories.

Understanding and Improving the Scale Dependence of Trigger Functions for Convective Parameterization Using Cloud-Resolving Model Data

AbstractAs the resolution of global climate model increases, whether trigger functions in current convective parameterization schemes still work remains unknown. In this study, the scale dependence of undilute and dilute dCAPE, Bechtold, and heated condensation framework (HCF) triggers is evaluated using the cloud-resolving model (CRM) data. It is found that all these trigger functions are scale dependent, especially for dCAPE-type triggers, with skill scores dropping from ~0.6 at the lower resolutions (128, 64, and 32 km) to only ~0.1 at 4 km. The average convection frequency decreases from 14.1% at 128 km to 2.3% at 4 km in the CRM data, but it increases rapidly in the dCAPE-type triggers and is almost unchanged in the Bechtold and HCF triggers across resolutions, all leading to large overpredictions at higher resolutions. In the dCAPE-type triggers, the increased frequency is due to the increased rate of dCAPE greater than the threshold (65 J kg−1 h−1) at higher resolutions. The box-and-whisker plots show that the main body of dCAPE in the correct prediction and overprediction can be separated from each other in most resolutions. Moreover, the underprediction is found to be corresponding to the decaying phase of convection. Hence, two modifications are proposed to improve the scale dependence of the undilute dCAPE trigger: 1) increasing the dCAPE threshold and 2) considering convection history, which checks whether there is convection prior to the current time. With these modifications, the skill at 16 km, 8 km, and 4 km can be increased from 0.50, 0.27, and 0.15 to 0.70, 0.61, and 0.53, respectively.

Linking Stochasticity of Convection to Large-Scale Vertical Velocity to Improve Indian Summer Monsoon Simulation in the NCAR CAM5

The Plant–Craig (PC) stochastic convective parameterization scheme is modified by linking the stochastic generation of convective clouds to the change of large-scale vertical pressure velocity at 500 hPa with time so as to better account for the relationship between convection and the large-scale environment. Three experiments using the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, version 5 (CAM5), are conducted: one with the default Zhang–McFarlane deterministic convective scheme, another with the original PC stochastic scheme, and a third with the modified PC stochastic scheme. Evaluation is focused on the simulation of the Indian summer monsoon (ISM), which is a long-standing challenge for all current global circulation models. Results show that the modified stochastic scheme better represents the annual cycle of the climatological mean rainfall over central India and the mean onset date of ISM compared to other simulations. Also, for the simulations of ISM intraseasonal variability for quasi-biweekly and 30–60-day modes, the modified stochastic parameterization produces more realistic propagation and magnitude, especially for the observed northeastward movement of the 30–60-day mode, for which the other two simulations show the propagation in the opposite direction. Causes are investigated through a moisture budget analysis. Compared to the other two simulations, the modified stochastic scheme with an appropriate representation of convection better represents the patterns and amplitudes of large-scale dynamical convergence and moisture advection and thus corrects the monsoon cycle associated with their covariation during the peaks and troughs of intraseasonal oscillation.

Isolating the Effects of Moisture Entrainment on Convectively Coupled Equatorial Waves in an Aquaplanet GCM

Abstract The rate of humidity entrainment in the convective parameterization scheme in a general circulation model affects the simulation of convectively coupled waves. However, it is unclear whether this is caused directly by the effects of entrainment on waves or indirectly through associated impacts such as on the basic state. Therefore, using an aquaplanet model, we employ a novel framework in which we entrain a weighted average of the resolved humidity field and a prescribed zonally symmetric field, with the weighting controlled by a decoupling parameter. Hence, we can vary the entrainment rate of basic-state humidity independently of the entrainment of humidity perturbations, simultaneously minimizing changes in the basic state. Thus, we isolate the effect of moisture entrainment on the waves. Enhancing the entrainment rate increases spectral power over all zonal wavenumbers and frequencies, with an increase in the ratio of eastward-to-westward power. The Kelvin wave speed decreases as entrainment increases, which can be partially accounted for by an associated change in basic-state humidity. Increasing the decoupling parameter reduces spectral power in Kelvin waves relative to the background, with only long waves still prominent when entrainment is almost fully decoupled from the resolved moisture field, suggesting the wave structure in humidity is required for convection to organize into short-wave structures. For long waves, the increase in the ratio of eastward-to-westward power as entrainment rate increases cannot be explained by the changes in the coupling with the wave structure in humidity but is consistent with the changes in the basic state.

WRF downscaling improves ERA-Interim representation of precipitation around a tropical Andean valley during El Niño: implications for GCM-scale simulation of precipitation over complex terrain

Precipitation in the tropical Andes is strongly influenced by the ENSO phases and orographic effects. In particular, precipitation can be drastically reduced during El Nino. Decision-making about water resources relies on modelling precipitation as the main source for water availability. Here we evaluate ERA-Interim´s capacity to represent precipitation in the mountainous central Colombian Andes, a strategic region for water supply and hydropower generation, for different phases of ENSO during 1998–2012. Our results show that ERA-Interim fails to reproduce important features of precipitation spatial and temporal variability during different ENSO phases. Most critical in these results is how ERA-Interim overestimates precipitation during the dry season in El Nino years, which corresponds to the most critical condition for water supply. We show that ERA-Interim limitations are likely related to its simplified representation of the complex topography in the region, which excludes the inter-Andean Cauca river valley. To improve this, we implement a dynamical downscaling experiment using the WRF regional climate model, including a sensitivity analysis that considers three convective parameterization schemes and a convection-permitting simulation. WRF downscaling outperforms ERA-Interim in the representation of precipitation during the dry season of El Nino years, especially through correcting positive precipitation biases. This improvement is related to a better representation of orographic effects in WRF simulations. Our results suggest that ERA-Interim and, more generally, climate simulations with comparable coarse resolutions, may produce misleading precipitation overestimations in the tropical Andes if they do not adequately represent inter-Andean valleys, with important implications for water resources management.

Performance of Regional Climate Model in Simulating Monsoon Onset Over Indian Subcontinent

The performance of various Convective Parameterization Schemes (CPSs) of Regional Climate Model version 4.3 (RegCM-4.3) for simulation of onset phase of Indian summer monsoon (ISM) over Kerala was studied for the period of 2001–2010. The onset date and its associated spatial variation were simulated using RegCM-4.3 four core CPS, namely Kuo, Tiedtke, Emanuel and Grell; and with two mixed convection schemes Mix98 (Emanuel over land and Grell over ocean) and Mix99 (Grell over land and Emanuel over ocean) on the basis of criteria given by the India Meteorological Department (IMD) (Pai and Rajeevan in Indian summer monsoon onset: variability and prediction. National Climate Centre, India Meteorological Department, 2007). It has been found that out of six CPS, two schemes, namely Tiedtke and Mix99 simulated the onset date properly. The onset phase is characterized with several transition phases of atmosphere. Therefore, to study the thermal response or the effect of different sea surface temperature (SST), namely ERA interim (ERSST) and weekly optimal interpolation (OI_WK SST) on Indian summer monsoon, the role of two different types of SST has been used to investigate the simulated onset date. In addition, spatial atmospheric circulation pattern during onset phase were analyzed using reanalyze dataset of ERA Interim (EIN15) and National Oceanic and Atmospheric Administration (NOAA), respectively, for wind and outgoing long-wave radiation (OLR) pattern. Among the six convective schemes of RegCM-4.3 model, Tiedtke is in good agreement with actual onset dates and OI_WK SST forcing is better for simulating onset of ISM over Kerala.

Explicit Convection and Scale-Aware Cumulus Parameterizations: High-Resolution Simulations over Areas of Different Topography in Germany

An increase in the spatial resolution of regional climate model simulations improves the representation of land surface characteristics and may allow the explicit calculation of important physical processes such as convection. The present study investigates further potential benefits with respect to precipitation, based on a small ensemble of high-resolution simulations with WRF with grid spacings up to 1 km. The skill of each experiment is evaluated regarding the temporal and spatial performance of the simulation of precipitation of one year over both a mountainous region in southwestern Germany and a mainly flat region in northern Germany. This study allows us to differentiate between the impact of grid spacing, topography, and convection parameterization. Furthermore, the performance of a state-of-the-art convection parameterization scheme in the gray zone of convection is evaluated against an explicit calculation of convection only. Our evaluation demonstrates the following: high-resolution simulations (5 and 1 km) are generally able to represent the diurnal cycle, structure, and intensity distribution of precipitation, when compared to observational datasets such as radar data and interpolated station data. The influence of the improved representation of the topography at higher resolution (1 km) becomes apparent in complex terrain, where the localization of precipitation maxima is more accurate, although these maxima are overestimated. In flat areas, differences in spatial evaluations arise between simulations with parameterized and explicitly calculated convection, whereas smaller grid spacings (1 km vs 5 km) show hardly any impact on precipitation results.

Combined impacts of convection and microphysics parameterizations on the simulations of precipitation and cloud properties over Asia

Convection and microphysics parameterization schemes (i.e. CPS and MPS) are two important components related to the precipitation and cloud simulations in climate models, and one parameterization's impacts on the results can be dependent on the treatments in the other one. This study investigates the individual and combined impacts of CPS and MPS on the precipitation and cloud simulations over Asia based on nine regional model experiments using combinations of three CPSs of the Kain–Fritsch (KF), Zhang–McFarlane (ZM), and Grell 3D ensemble (G3), and three MPSs of the WRF double-moment 5-class (WDM5), WRF double-moment 6-class (WDM6), and Morrison double-moment (MORR). We first evaluate the simulated precipitation and find the experiment configured with the ZM CPS and MORR MPS performs the best when considering both the precipitation mean magnitude and spatial pattern. The sensitivity analysis results show that enhanced convection due to changing the CPS can cause strengthened or weakened stratiform processes, depending on the height of convective detrainments relative to that of convective drying, which is different among CPSs. In general, the CPS impacts on precipitation and clouds are larger when associating with the MORR MPS than with the other two MPSs as the former simulates more clouds and exhibits larger sensitivity of stratiform-type drying to convective detrainments. The MPS impacts on the precipitation and cloud simulations are also highly related to the CPS's behavior in simulating ice detrainments. Compared to the sum of the individual effects of CPS and MPS, simultaneously changing the two parameterizations causes considerably larger impacts on the precipitation and cloud simulations, suggesting the strong nonlinear interaction between the CPS and MPS.

Regional Climate Model Performance in Simulating Intra-seasonal and Interannual Variability of Indian Summer Monsoon

Establishment of Indian summer monsoon (ISM) rainfall passes through the different phases and is not uniformly distributed over the Indian subcontinent. This enhancement and reduction in daily rainfall anomaly over the Indian core monsoon region during peak monsoon season (i.e., July and August) are commonly termed as ‘active’ and ‘break’ phases of monsoon. The purpose of this study is to analyze REGional Climate Model (RegCM) results obtained using the most suitable convective parameterization scheme (CPS) to determine active/break phases of ISM. The model-simulated daily outgoing longwave radiation (OLR), mean sea level pressure (MSLP), and the wind at 850 hPa of spatial resolution of 0.5°× 0.5° are compared with NOAA, NCEP, and EIN15 data, respectively over the South-Asia Co-Ordinated Regional Climate Downscaling EXperiment (CORDEX) region. 25 years (1986–2010) composites of OLR, MSLP, and the wind at 850 hPa are considered from start to the dates of active/break phase and up to the end dates of active/break spell of monsoon. A negative/positive anomaly of OLR with active/break phase is found in simulations with CPSs Emanuel and Mix99 (Grell over land; Emanuel over ocean) over the core monsoon region as well as over Monsoon Convergence Zone (MCZ) of India. The appearance of monsoon trough during active phase over the core monsoon zone and its shifting towards the Himalayan foothills during break phase are also depicted well. Because of multi-cloud function over oceanic region and single cloud function over the land mass, the Mix99 CPSs perform well in simulating the synoptic features during the phases of monsoon.

How Well Can We Represent the Spectrum of Convective Clouds in a Climate Model? Comparisons between Internal Parameterization Variables and Radar Observations

Current climate models cannot resolve individual convective clouds, and hence parameterizations are needed. The primary goal of convective parameterization is to represent the bulk impact of convection on the gridbox-scale variables. Spectral convective parameterizations also aim to represent the key features of the subgrid-scale convective cloud field such as cloud-top-height distribution and in-cloud vertical velocities in addition to precipitation rates. Ground-based radar retrievals of these quantities have been made available at Darwin, Australia, permitting direct comparisons of internal parameterization variables and providing new observational references for further model development. A spectral convective parameterization [the convective cloud field model (CCFM)] is discussed, and its internal equation of motion is improved. Results from the ECHAM–HAM model in single-column mode using the CCFM and the bulk mass flux Tiedtke–Nordeng scheme are compared with the radar retrievals at Darwin. The CCFM is found to outperform the Tiedtke–Nordeng scheme for cloud-top-height and precipitation-rate distributions. Radar observations are further used to propose a modified CCFM configuration with an aerodynamic drag and reduced entrainment parameter, further improving both the convective cloud-top-height distribution (important for large-scale impact of convection) and the in-cloud vertical velocities (important for aerosol activation). This study provides a new development in the CCFM, improving the representation of convective cloud spectrum characteristics observed in Darwin. This is a step toward an improved representation of convection and ultimately of aerosol effects on convection. It also shows how long-term radar observations of convective cloud properties can help constrain parameters of convective parameterization schemes.

Improvement in the Modeled Representation of North American Monsoon Precipitation Using a Modified Kain–Fritsch Convective Parameterization Scheme

A commonly noted problem in the simulation of warm season convection in the North American monsoon region has been the inability of atmospheric models at the meso-β scales (10 s to 100 s of kilometers) to simulate organized convection, principally mesoscale convective systems. With the use of convective parameterization, high precipitation biases in model simulations are typically observed over the peaks of mountain ranges. To address this issue, the Kain–Fritsch (KF) cumulus parameterization scheme has been modified with new diagnostic equations to compute the updraft velocity, the convective available potential energy closure assumption, and the convective trigger function. The scheme has been adapted for use in the Weather Research and Forecasting (WRF). A numerical weather prediction-type simulation is conducted for the North American Monsoon Experiment Intensive Observing Period 2 and a regional climate simulation is performed, by dynamically downscaling. In both of these applications, there are notable improvements in the WRF model-simulated precipitation due to the better representation of organized, propagating convection. The use of the modified KF scheme for atmospheric model simulations may provide a more computationally economical alternative to improve the representation of organized convection, as compared to convective-permitting simulations at the kilometer scale or a super-parameterization approach.