Impact of a scale-aware convective parameterization scheme on the simulation of convective cells related heavy rainfall in South Korea

2021 ◽  
Author(s):  
Haerin Park ◽  
Gayoung Kim ◽  
Dong-Hyun Cha ◽  
Eun-Chul Chang ◽  
Joowan Kim ◽  
...  
Keyword(s):  
South Korea ◽  
Heavy Rainfall ◽  
Parameterization Scheme ◽  
Convective Parameterization ◽  
Convective Parameterization Scheme ◽  
Convective Cells

scholarly journals Using Betts-Miller-Janjic convective parameterization scheme in H14-31 model to forecast heavy rainfall in Vietnam

2007 ◽  
Vol 29 (2) ◽  
pp. 83-97
Author(s):  
Vu Thanh Hang ◽  
Kieu Thi Xin
Keyword(s):  
Heavy Rainfall ◽  
Precipitation Forecast ◽  
Parameterization Scheme ◽  
Model Resolution ◽  
Convective Parameterization ◽  
Rainfall Forecast ◽  
Quantitative Precipitation Forecast ◽  
Convective Adjustment ◽  
Convective Parameterization Scheme ◽  
The Tropics

According to Krishnamurti, improvements of physical parameterizations will mainly affect simulations for the tropics [10]. The study of William A. Gallus Jr. showed that the higher the model resolution and more detailed convective parameterizations, the better the skill in quantitative precipitation forecast (QPF) in general [16]. The quality of precipitation forecast is so sensitive to convective parameterization scheme (CPS) used in the model as well as model resolution. The fact shows that for high resolution regional model like H14-31 CPS based on low-level moisture convergence as Tiedtke did not give good heavy rainfall forecast in Vietnam. In this paper we used the scheme of Betts-Miller-Janjic (BMJ) based on the convective adjustment toward tropical observationally structures in reality instead of Tiedtke in Hl4-31. Statistical verification results and verification using CRA method of Hl4-31 of two CPSs for seperated cases and for three rain seasons (2003-2005) shows that heavy rainfall forecast of Hl4-31/BMJ is better than one of H14-31/TK for Vietnam-South China Sea. CRA verification also shows that it is possible to say that heavy rainfall forecast skill of l-I14-31/BMJ in tropics is nearly similar to the skill of LAPS of Australia.

scholarly journals Suppressing Grid-Point Storms in a Numerical Forecasting Model

Atmosphere ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1194
Author(s):  
Seung-Bu Park ◽  
Ji-Young Han
Keyword(s):  
Grid Point ◽  
Parameterization Scheme ◽  
Western Pacific Ocean ◽  
Convection Scheme ◽  
Convective Parameterization ◽  
Tropical Oceans ◽  
Test Version ◽  
Convective Parameterization Scheme ◽  
Case Simulation ◽  
The Western Pacific

The convective parameterization scheme of the Korean Integrated Model (KIM) is tentatively modified to suppress grid-point storms in the Western Pacific Ocean. The KIM v3.2.11 suffers from the numerical problem that grid-point storms degrade forecasts in the tropical oceans and around the Korean Peninsula. Another convective parameterization scheme, the new Tiedtke scheme, is implemented in the KIM. The artificial storms are suppressed in the test version because the heating and drying tendencies of the new Tiedtke scheme are stronger than those of the default KIM Simplified Arakawa-Schubert (KSAS) scheme. Based on this comparison, the KSAS scheme is modified to strengthen its heating and drying tendencies by reducing the entrainment and detrainment rates. The modified KSAS scheme suppresses grid-point storms and thus decreases grid-scale precipitation in a summertime case simulation. Twenty 10-day forecasts with the default convection scheme (KSAS) and twenty forecasts with the modified scheme are conducted and compared with each other, confirming that the modified KSAS scheme successfully suppresses grid-point storms.

scholarly journals Some issues in uncertainty quantification and parameter tuning: a case study of convective parameterization scheme in the WRF regional climate model

2012 ◽  
Vol 12 (5) ◽  
pp. 2409-2427 ◽  
Author(s):  
B. Yang ◽  
Y. Qian ◽  
G. Lin ◽  
R. Leung ◽  
Y. Zhang
Keyword(s):  
Uncertainty Quantification ◽  
Spatial Scales ◽  
Wrf Model ◽  
Parameter Tuning ◽  
Parameterization Scheme ◽  
Convective Precipitation ◽  
Optimal Parameters ◽  
Convective Parameterization ◽  
Input Parameters ◽  
Convective Parameterization Scheme

Abstract. The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. While the latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic importance sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment-related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreased as the ratio of downdraft to updraft flux increased. Larger CAPE consumption time resulted in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by constraining only precipitation generated positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25-km simulation, both the magnitude and spatial pattern of simulated precipitation were improved at 12-km spatial resolution. The optimal parameters identified from the SGP region also improved the simulation of precipitation when the model domain was moved to another region with a different climate regime (i.e. the North America monsoon region). These results suggest that benefits of optimal parameters determined through vigorous mathematical procedures such as the MVFSA process are transferable across processes, spatial scales, and climatic regimes to some extent. This motivates future studies to further assess the strategies for UQ and parameter optimization at both global and regional scales.

scholarly journals Evaluation of MM5 High-Resolution Real-Time Forecasts over the Urban Area of Athens, Greece

2004 ◽  
Vol 43 (11) ◽  
pp. 1666-1678 ◽  
Author(s):  
V. Kotroni ◽  
K. Lagouvardos
Keyword(s):  
Surface Temperature ◽  
Heat Waves ◽  
Thunderstorm Activity ◽  
Forecast Skill ◽  
Precipitation Forecast ◽  
Parameterization Scheme ◽  
Cold Bias ◽  
Near Surface ◽  
Convective Parameterization ◽  
Convective Parameterization Scheme

Abstract In this paper the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) forecast skill over an area of complex terrain is evaluated. Namely, the model is verified over a period of 1 yr (2002) over the greater area of Athens, Greece, for its near-surface temperature and wind forecasts, at 8- and 2-km grid spacing, but also over a 15-day period for the summer thunderstorm activity forecasts. For the near-surface temperature a cold bias is evident. The model is, in general, unable to reproduce the summer heat waves observed in the area. The increase of the grid resolution, from 8 to 2 km, results in an improvement of the forecast skill. Postprocessing of the forecasts by applying a Kalman-filtering correction method was very effective for both the 8- and the 2-km forecasts. For the forecast skill of wind, the analysis showed that there is not any net increase of the errors with increasing forecast time for the 48-h forecast period, the mean absolute errors, in general, present the lowest values at noontime, and the increase in resolution, from 8 to 2 km, results in a slight decrease of these errors. The analysis of the model skill to accurately forecast summertime precipitation showed that the 2-km simulations, without activation of the convective parameterization scheme, were unable to reproduce the observed thunderstorm activity. Sensitivity tests for the same period with simulations in which the convective parameterization was not activated for both the 8- and the 2-km simulations were still inaccurate, while activation of the convective parameterization scheme at all grids (even at 2 km) considerably increased the precipitation forecast skill.

The parameterization of slantwise convection in a numerical model

2021 ◽  
Author(s):  
Ting-Chen Chen ◽  
Man-Kong Yau ◽  
Daniel J. Kirshbaum
Keyword(s):  
Large Scale ◽  
Weather Forecasting ◽  
Wrf Model ◽  
Parameterization Scheme ◽  
Weather Research And Forecasting ◽  
Natural State ◽  
Convective Parameterization ◽  
Scale Models ◽  
Convective Parameterization Scheme ◽  
Slantwise Convection

<p>     Slantwise convection and the associated release of conditional symmetric instability (CSI) have been recognized as important baroclinic processes. Recent climatological studies have highlighted its significant association with midlatitude cyclone activities, raising questions about whether large-scale models can resolve slantwise convection and whether it should be parameterized.</p><p>     To address this issue, the present study simulates isolated free moist slantwise convection in an initially statically stable environment using the 2D idealized, non-hydrostatic Weather Research and Forecasting (WRF) Model. We first examined the sensitivity of the slantwise convection to the cross-band grid spacing (Δy; varied from 40 to 1 km) and found that experiments with ∆y> 5 km fail to capture the band dynamics and larger-scale feedbacks robustly and thus require parameterization. As most of the current convective parameterization schemes target upright convection in a local column, we implemented an additional 2D slantwise convective parameterization scheme and evaluated its impact for coarse-grid runs.</p><p>     The slantwise convective parameterization scheme operates along a sloped trajectory on a horizontally-variant cross section perpendicular to the local thermal wind, adjusting the environment toward a natural state to CSI within a given time scale. With the addition of the slantwise convective parameterization scheme, significant improvements are found in precipitation and the strength of the slantwise updraft, bringing the coarser-grid (∆y=40 km) simulation closer to the finer-grid (converged) results than its counterpart with only the upright convection scheme. After testing the slantwise convective parameterization scheme under idealized frameworks, we will further apply it to regional models to evaluate its benefit to the weather forecasting in real cases.</p>

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