A sensitivity study of WRF model microphysics and cumulus parameterization schemes for the simulation of tropical cyclones using GPM radar data

Baki, Harish; Chinta, Sandeep; Balaji, C.; Srinivasan, Balaji

doi:10.1007/s12040-021-01682-3

Cited by 9 publications

(8 citation statements)

References 46 publications

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“…The Purdue Lin scheme includes all hydrometer including graupel. This scheme is widely used for better reproduce the MCS characteristics during convection and heavy rainfall, and cost less calculation resources than other schemes (Baki et al., 2021; Shi et al., 2021). Besides, we use the Yonsei University planetary boundary layer scheme (Hong et al., 2006), the Monin‐Obukhov surface layer scheme, the Noah land‐surface model, and the single‐layer urban canopy model, the Rapid Radiative Transfer Model for General Circulation Models longwave and shortwave radiation transport scheme (Iacono et al., 2008).…”

Section: Model Data and Methodsmentioning

confidence: 99%

Responses of Mesoscale Convective System to Global Warming: A Study on the Henan 2021 Record‐Breaking Rainfall Event

Lin,

Nie,

Wang

et al. 2024

JGR Atmospheres

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The limited capabilities of global climate models in simulating mesoscale convective systems (MCSs) restrict our understanding of how global warming impacts MCSs. This study uses a high‐resolution numerical model with large‐ensemble experiments to simulate MCSs during the record‐breaking extreme rainfall event in Henan Province, China, in July 2021. We compare the changes in the MCS's strength, size, and structure in a real‐world simulation (RW) and a 0.8°C colder simulation (analog to no‐anthropogenic‐warming‐world simulation, short for NAWW) to assess the response of MCSs to global warming. Our results show that the total rainfall from the MCS increased by 10.0% in RW compared to NAWW, with a 3.1% increase in area and a 6.7% increase in rainfall intensity. The development of MCS becomes more rapid in response to warming since the pre‐industrial era. The warmer and wetter climate results in higher convective available potential energy, and accelerates the MCS growth, but then the narrower low‐convective inhibition regions suppress the continuous growth of MCS. During the mature phase, the maximum hourly rainfall intensity (Pmax) can increase by up to 26.5%/K, while Pmax locations can either remain unchanged or shift depending on the interaction of flows and terrains. These results highlight varying responses of MCSs to global warming during its different stages and provide valuable insights into the changing characteristics of extreme rainfall events under global warming.

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Section: Model Data and Methodsmentioning

confidence: 99%

Responses of Mesoscale Convective System to Global Warming: A Study on the Henan 2021 Record‐Breaking Rainfall Event

Lin,

Nie,

Wang

et al. 2024

JGR Atmospheres

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“…The parameter for computing the amount of cloud cover in saturated conditions (uc1) from the radiation scheme, qi0 from microphysics, mean entrainment rate for shallow convection (entr_sc) from the convection scheme and factor for turbulent momentum dissipation (d_mom) from turbulence scheme are the next set sensitive parameters to simulate TP by the model as evident from the changes in SS against the default values (Figure 7b). Two recent studies identify the model parameter defined as the multiplier for entrainment flux rate as the most significant to reproduce precipitation in high-intensity precipitation events by Weather Research Forecasting (WRF) model [46,48,[71][72][73] . 1) calculated against the reference simulation (parameter values in bold shown in Table 1) for T2M as a function of domains.…”

Section: Model Performances In Different Domainsmentioning

confidence: 99%

Evaluation of COSMO-CLM Model Parameter Sensitivity in the Study of Extreme Events across the Eastern Region of India

Bal,

Kirchner

2024

j. of atmos. sci. res.

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The present study aims to identify the parameters from the Consortium for Small-scale Modelling in CLimate Mode (COSMO-CLM) regional climate model that strongly controls the prediction of extreme events over West Bengal and the adjoining areas observed between 2013 to 2018. Metrics, namely Performance Score (PS) screen out the most persuasive parameter on model output. Additionally, the Performance Index (PI) measure the reliability of the model and Skill Score (SS) establishes the model performance against the reference simulation leading to the optimization of the model for a given variable. In this study, parameter screening for four output variables such as 2m-temperature, surface latent heat flux, precipitation and cloud cover of COSMO-CLM is accomplished. For heat wave simulations, 2m-temperature and surface latent heat flux are explored whereas cloud cover and precipitation are examined for extreme rainfall events. A total of 25 adjustable parameters representing the following parameterization schemes: turbulence, land surface process, microphysics, convection, radiation and soil. Out of the six parameterization schemes, the scaling factor of the laminar boundary layer for heat (rlam_heat) and the ratio of laminar scaling factors for heat over sea and land (rat_sea) from the land surface process is sensitive to SLH, TP. The exponent to get the effective surface area (e_surf) from the land surface has a large impact on 2m-temperature. A few parameters from microphysics (cloud ice threshold for auto conversion), convection (mean entrainment rate for shallow convection) and radiation (parameter for computing the amount of cloud cover in saturated conditions) play a significant role in producing TP, and TCC fields. It is evident from the results that the parameter sensitivities on model performance depend on the choice of the meteorological field. Furthermore, in almost all input model parameters, the model performance reveals the opposite character in different domains for a given meteorological field.

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“…It is acknowledged that estimation of rainfall over a certain region in an atmospheric model is strongly dependent on CU and MP parameterizations. Many studies have revealed that applying different combinations of cumulus and microphysics options in a model for a region can yield different results [49,50]. In this study, we designed, in total, 9 combinations of CU and MP parameterizations by which three CU schemes, namely Betts-Miller-Janjic (BMJ), Grell 3D Ensemble (G3), and Kain-Fritsch (KF) along with three MP schemes, namely Eta Ferrier (ETA), Purdue Lin (LIN), and WRF Single-moment 3-class (WSM3), are selected for the sensitivity analysis.…”

Section: Combinations Of Cu and Mpmentioning

confidence: 99%

Simulating Heavy Rainfall Associated with Tropical Cyclones and Atmospheric Disturbances in Thailand using the Coupled WRF-ROMS Model - Sensitivity Analysis of Microphysics and Cumulus Parameterization Schemes

Torsri¹,

Faikrua²,

Peangta³

et al. 2023

Preprint

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This study aims to identify the optimal combination of microphysics (MP) and cumulus (CU) parameterization schemes for accurately simulating heavy to violet rainfall events associated with Tropical Cyclones (TCs) and atmospheric disturbances in Thailand using the coupled Weather Research and Forecasting (WRF) and Regional Oceanic Model (ROMS), hereafter referred to as WRF-ROMS. Three CU schemes, namely Betts–Miller–Janjic (BMJ), Grell 3D Ensemble (G3), and Kain–Fritsch (KF), along with three MP schemes, namely Eta (ETA), Purdue Lin (LIN), and WRF Single-moment 3-class (WSM3), are selected for the sensitivity analysis. Seven instances of heavy to violent rainfall in Thailand, occurring during summer season of 2020 and associated with tropical storms and atmospheric disturbances, are simulated using all possible combinations of the chosen physics schemes. The simulated rain intensities are compared against observations from the National Hydroinformatics Data Center. Performance was assessed using the Probability of Detection (POD), False Alarm Ratio (FAR), and Critical Success Index (CSI) metrics. The models showed proficiency in predicting light to moderate rainfall, with certain combinations performing better in specific rainfall categories. However, forecasting heavy and violent rainfall proved challenging for all models and lead-time forecasts. Specific combinations, particularly those incorporating the KF scheme, demonstrated superior prediction of heavy to violent rainfall. The FAR values increased with lead-time and rain intensity, and the KF scheme combinations showed improved predictions of intense rainfall with lower FAR values. The CSI values indicated comparable performance between the control model and combination models across light to heavy rain categories, with the KF scheme showing better predictions for longer lead-times. However, accurately predicting intense rainfall remained limited. These findings highlight the need for further improvements, including refining model parameters and exploring advanced techniques to enhance accuracy and skill, particularly for longer-term forecasts. Sub-seasonal to seasonal prediction should be considered to extend forecast capabilities.

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A sensitivity study of WRF model microphysics and cumulus parameterization schemes for the simulation of tropical cyclones using GPM radar data

Cited by 9 publications

References 46 publications

Responses of Mesoscale Convective System to Global Warming: A Study on the Henan 2021 Record‐Breaking Rainfall Event

Responses of Mesoscale Convective System to Global Warming: A Study on the Henan 2021 Record‐Breaking Rainfall Event

Evaluation of COSMO-CLM Model Parameter Sensitivity in the Study of Extreme Events across the Eastern Region of India

Simulating Heavy Rainfall Associated with Tropical Cyclones and Atmospheric Disturbances in Thailand using the Coupled WRF-ROMS Model - Sensitivity Analysis of Microphysics and Cumulus Parameterization Schemes

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