Sensitivity of precipitation and temperature over the Mount Kenya area to physics parameterization options in a high-resolution model simulation performed with WRFV3.8.1

Several sensitivity experiments with the Weather Research and Forecasting (WRF) model version 3.8.1 have been performed to find the optimal parameterization setup for precipitation amounts and patterns around Mount Kenya at a convection-permitting scale of 1 km. Hereby, the focus is on the cumulus scheme, with tests of the Kain–Fritsch, the Grell–Freitas, and no cumulus parameterizations. In addition, two longwave radiation schemes and two planetary boundary layer parameterizations are evaluated, and different nesting ratios and numbers of nests are tested. The precipitation amounts and patterns are compared against a large amount of weather station data and three gridded observational data sets. The temporal correlation of monthly precipitation sums show that fewer nests lead to a more constrained simulation, and hence the correlation is higher. The pattern correlation with weather station data confirms this result, but when comparing it to the most recent gridded observational data set the difference between the number of nests and nesting ratios is marginal. The precipitation patterns further reveal that using the Grell–Freitas cumulus parameterization in the domains with resolutions >5 km provides the best results when it comes to precipitation patterns and amounts. If no cumulus parameterization is used in any of the domains, the temporal correlation between gridded and in situ observations and simulated precipitation is especially poor with more nests. Moreover, even if the patterns are captured reasonably well, a clear overestimation in the precipitation amounts is simulated around Mount Kenya when using no cumulus scheme in all domains. The experiment with the Grell–Freitas cumulus parameterization in the domains with resolutions >5 km also provides reasonable results for 2 m temperature with respect to gridded observational and weather station data.

Sensitivity of precipitation and temperature over Mount Kenya area to physics parameterization options in a high-resolution model simulation performed with WRFV3.8.1

Several sensitivity experiments with the Weather Research and Forecasting (WRF) model version 3.8.1 have been performed to find the optimal parameterization setup for precipitation amounts and patterns around Mount Kenya at a convection-permitting scale of 1 km. Hereby, the focus is on the cumulus scheme, with tests of the Kain-Fritsch, the Grell-Freitas and no cumulus parameterization for the parent and all nested domains. Besides, two long wave radiation schemes and two planetary boundary layer parameterizations are evaluated. Additionally, different nesting ratios and numbers of nests are tested. The precipitation amounts and patterns are compared against a large number of weather station data and three gridded observational data sets. The temporal correlation of monthly precipitation sums show that fewer nests lead to a more constrained simulation and hence, the correlation is higher. The pattern correlation with weather station data confirms this result, but when comparing it to the most recent gridded observational data set the difference between the number of nests and nesting ratios are marginal. The precipitation patterns further reveal that the Grell-Freitas cumulus parameterization provides the best results, when it comes to precipitation patterns and amounts. If no cumulus parameterization is used, the temporal correlation between gridded and in-situ observations and simulated precipitation is especially poor with more nests. Moreover, even if the patterns are captured quite well, a clear overestimation in the precipitation amounts is observed around Mount Kenya when using no cumulus scheme at all. The Grell-Freitas cumulus parameterization also provides reasonable results for 2-metre temperature with respect to gridded observational and weather station data.

Model Improvement via Systematic Investigation of Physics Tendencies

Deficiencies in forecast models commonly stem from inadequate representation of physical processes; yet, improvement to any single physics component within a model may lead to degradations in other physics components or the model as a whole. In this study, a systematic investigation of physics tendencies is demonstrated to help identify and correct compensating sources of model biases. The model improvement process is illustrated by addressing a commonly known issue in warm-season rainfall forecasts from parameterized convection models: the misrepresentation of the diurnal precipitation cycle over land, especially in its timing. Recent advances in closure assumptions in mass-flux cumulus schemes have made remarkable improvements in this respect. Here, we investigate these improvements in the representation of the diurnal precipitation cycle for a spring period over the United States, and how changes to the cumulus scheme impact the model climate and the behavior of other physics schemes. The modified cumulus scheme improves both the timing of the diurnal precipitation cycle and reduces midtropospheric temperature and moisture biases. However, larger temperature and moisture biases are found in the boundary layer as compared to a predecessor scheme, along with an overamplification of the diurnal precipitation cycle, relative to observations. Guided by a tendency analysis, we find that biases in the diurnal amplitude of the precipitation cycle in our simulations, along with temperature and moisture biases in the boundary layer, originate from the land surface model.

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

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.

Impacts of Different Cumulus Schemes on the Pathways through which SST Provides Feedback to the Madden–Julian Oscillation

Six sets of hindcasts conducted with the NCEP GFS have been used to study the SST-feedback processes and assess the relative contributions of atmospheric internal dynamics and SST feedback on the October and November MJO events observed during the DYNAMO IOP (Oct- and Nov-MJO). The hindcasts are carried out with three variants of the Arakawa–Shubert cumulus scheme under TMI and climatological SST conditions. The positive intraseasonal SST anomaly along with its convergent Laplacian produces systematic surface disturbances, which include enhanced surface convergence, evaporation, and equivalent potential temperature no matter which cumulus scheme is used. Whether these surface disturbances can grow into a robust response of MJO convection depends on the characteristics of the cumulus schemes used. If the cumulus scheme is able to amplify the SST-initiated surface disturbances through a strong upward–downward feedback, the model is able to produce a robust MJO convection response to the underlying SST anomaly; otherwise, the model will not produce any significant SST feedback. A new method has been developed to quantify the “potential” and “practical” contributions of the atmospheric internal dynamics and SST feedback on the MJOs. The present results suggest that, potentially, the SST feedback could have larger contributions than the atmospheric internal dynamics. Practically, the contributions to the Oct- and Nov-MJO events are, respectively, dominated by atmospheric internal dynamics and SST feedback. Averaged over the entire period, the contributions from the atmospheric internal dynamics and SST feedback are about half and half.

A Study on the Influences of Low-Frequency Vorticity on Tropical Cyclone Formation in the Western North Pacific

The WRF Model is used to simulate 52 tropical cyclones (TCs) that formed in the western North Pacific during 2008–09 to study the influence of the low-frequency mode of environmental vorticity on TC formation [ Vmax ~ 25 kt (~13 m s−1)]. All simulations, using the same model setting, are repeated at four distinct initial times and with two different initial datasets. These TCs are classified into two groups based on the environmental 850-hPa low-frequency vorticity (using a 10-day low-pass filter) during the period 24–48 h prior to TC formation. Results show that the WRF Model is more capable of simulating the TC formation process, but with larger track errors for TCs formed in an environment with higher low-frequency vorticity (HTC). In contrast, the model is less capable of simulating the TC formation process for TCs formed in an environment with lower low-frequency vorticity (LTC), but with smaller track errors. Fourteen selected TCs are further simulated to examine the sensitivity of previous results to different cumulus parameterization schemes. Results show that the capability of the WRF Model to simulate HTC formation is not sensitive to the choice of cumulus scheme. However, for an LTC, the simulated convection pattern is very sensitive to the cumulus scheme used; therefore, model simulation capability for LTC depends on the cumulus scheme used. Results of this study reveal that the convection process is not a dominant factor in HTC formation, but is very important for LTC formation.

A Spectral Cumulus Parameterization Scheme Interpolating between Two Convective Updrafts with Semi-Lagrangian Calculation of Transport by Compensatory Subsidence

The authors have developed a new spectral cumulus parameterization scheme that explicitly considers an ensemble of multiple convective updrafts by interpolating in-cloud variables between two convective updrafts with large and small entrainment rates. This cumulus scheme has the advantages that the variables in entraining and detraining convective updrafts are calculated in detail layer by layer as in the Tiedtke scheme, and that a spectrum of convective updrafts with different heights due to the difference in entrainment rates is explicitly represented, as in the Arakawa–Schubert scheme. A conservative and monotonic semi-Lagrangian scheme is used for calculation of transport by convection-induced compensatory subsidence. Use of the semi-Lagrangian scheme relaxes the mass-flux limit due to the Courant–Friedrichs–Lewy (CFL) condition, and moreover ensures nonnegative natural material transport. A global atmospheric model using this cumulus scheme gives an atmospheric simulation that agrees well with the observational climatology.

Numerical Simulations of the 1 May 2012 Deep Convection Event over Cuba: Sensitivity to Cumulus and Microphysical Schemes in a High-Resolution Model

This paper evaluates the sensitivity to cumulus and microphysics schemes, as represented in numerical simulations of the Weather Research and Forecasting model, in characterizing a deep convection event over the Cuban island on 1 May 2012. To this end, 30 experiments combining five cumulus and six microphysics schemes, in addition to two experiments in which the cumulus parameterization was turned off, are tested in order to choose the combination that represents the event precipitation more accurately. ERA Interim is used as lateral boundary condition data for the downscaling procedure. Results show that convective schemes are more important than microphysics schemes for determining the precipitation areas within a high-resolution domain simulation. Also, while one cumulus scheme captures the overall spatial convective structure of the event more accurately than others, it fails to capture the precipitation intensity. This apparent discrepancy leads to sensitivity related to the verification method used to rank the scheme combinations. This sensitivity is also observed in a comparison between parameterized and explicit cumulus formation when the Kain-Fritsch scheme was used. A loss of added value is also found when the Grell-Freitas cumulus scheme was activated at 1 km grid spacing.

Simulation of a Heavy Rainfall Event on 14 September 2004 over Dhaka, Bangladesh Using MM5 Model

An attempt has been made to simulate a heavy rainfall event on 14 September 2004 over Dhaka, Bangladesh using the fifth-generation PSU/NCAR Mesoscale model (MM5). This was an extraordinary rainfall event and recorded 341 mm rainfall in 24-h which was the highest ever recorded. The MM5 model was run on triple-nested domains at 45, 15, 5 km horizontal resolutions using Anthes-Kuo cumulus scheme. The model performance was evaluated by examining the different predicted parameters like mean sea level pressure, upper and lower level circulations, moisture, windshear, vorticity, convergence and rainfall. The model derived rainfall was compared with TRMM rainfall. The present results indicate that the MM5 model with the right combination of the nesting domain, horizontal resolution and cumulus scheme was able to simulate the heavy rainfall event, and associated dynamical and thermo-dynamical features reasonably well. The MM5 model suggested that the highly localized heavy rain over Dhaka was the result of an interaction of the monsoon land depression with southwest summer monsoon weather systems. The analysis shows that the depression almost remains stationary over southwest Bangladesh and zone of heavy rain was laid over Dhaka, and required moisture have been supplied from the Bay of Bengal.Keywords: Depression; Heavy rainfall; TRMM; MM5 model; High resolution.© 2011 JSR Publications. ISSN: 2070-0237 (Print); 2070-0245 (Online). All rights reserved.doi:10.3329/jsr.v3i2.6656 J. Sci. Res. 3 (2), 261-270 (2011)