Sensitivity of simulated extreme precipitation and temperature to convective parameterization using RegCM3 in China

Hui, Pinhong; Tang, Jianping; Wang, Shuyu; Wu, Jian

doi:10.1007/s00704-014-1300-2

Cited by 12 publications

(9 citation statements)

References 66 publications

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“…In general, the range of biases seen in our simulations is comparable with previous studies based on earlier versions of RegCM (e.g. Hui et al 2015;Ji and Kang 2015;Gao et al 2016;Gao et al 2017). The D2 simulations driven by D1-NoHyd tend to reduce the systematic biases compared to those driven D1-Hyd.…”

Section: Climatological Pattern Of Summer Temperature and Precipitationsupporting

confidence: 89%

Evaluation of the performance of non-hydrostatic RegCM4 (RegCM4-NH) over China

Nguyen-Xuan

Lam

Giorgi

et al. 2021

Preprint

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This study evaluates the performance of the latest version of non-hydrostatic RegCM4 (RegCM4-NH) customized over two vast urban agglomerations in China (i.e., the Pearl River Delta, PRD, and the Yangtze River Delta, YRD). The analysis focuses on how the dynamical core (hydrostatic versus non-hydrostatic) employed in the driving mother domain simulation can affect the regional characteristics of temperature and precipitation patterns in the PRD and YRD regions simulated by a 4 km resolution nested RegCM4-NH. In addition, we assess the sensitivity of the 4 km model results to the use of a convective parameterization scheme (CPS), since the 4 km grid size can be considered as a gray-zone resolution at which deep convection is partially resolved and may still need to be parameterized. For mean temperature, a reasonable performance is shown by all simulations, with the summer season mean bias mostly less than ±1°C when averaged over the PRD and YRD. However, the simulated daily temperature distribution is excessively peaked around the median value, indicating a large probability concentrated on a small temperature range. Although the higher resolution slightly ameliorates this deficiency, the effect of the dynamical core and CPS tends to be marginal. Conversely, precipitation behaves quite differently across simulations. The driving forcing from the non-hydrostatic mother domain simulation helps to reduce a severe dry bias seen over the PRD due to a reduction in convection inhibition. Use of the Emanuel CPS also tends to intensify localized precipitation events over mountainous regions in connection with stronger ascending motions over topographical features. The higher resolution also improves the phase of the diurnal cycle of precipitation, both with and without the use of the CPS. In general, the performance of RegCM4-NH over the PRD and YRD is found to be best when driven by a non-hydrostatic mother domain simulation and when turning on the Emanuel CPS.

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Section: Climatological Pattern Of Summer Temperature and Precipitationsupporting

confidence: 89%

Evaluation of the performance of non-hydrostatic RegCM4 (RegCM4-NH) over China

Nguyen-Xuan

Lam

Giorgi

et al. 2021

Preprint

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“…The SDSM‐downscaled results show good agreement with the observations, with relative biases of less than 75% over most regions, whereas the biases in the WRF simulations are larger. The biases in the WRF simulations indicate the impact of driving GCMs in regional climate downscaling [ Déqué et al ., ; Gao et al ., , ] and the importance of the intermodel physics, such as the land surface process [ Sato and Xue , ; Bao et al ., ] and cumulus physics [ Hui et al ., ].…”

Section: Comparison Of Statistically and Dynamically Downscaled Regiomentioning

confidence: 99%

Statistical downscaling and dynamical downscaling of regional climate in China: Present climate evaluations and future climate projections

et al. 2016

Self Cite

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Statistical downscaling and dynamical downscaling are two approaches to generate high‐resolution regional climate models based on the large‐scale information from either reanalysis data or global climate models. In this study, these two downscaling methods are used to simulate the surface climate of China and compared. The Statistical Downscaling Model (SDSM) is cross validated and used to downscale the regional climate of China. Then, the downscaled historical climate of 1981–2000 and future climate of 2041–2060 are compared with that from the Weather Research and Forecasting (WRF) model driven by the European Center‐Hamburg atmosphere model and the Max Planck Institute Ocean Model (ECHAM5/MPI‐OM) and the L'Institut Pierre‐Simon Laplace Coupled Model, version 5, coupled with the Nucleus for European Modelling of the ocean, low resolution (IPSL‐CM5A‐LR). The SDSM can reproduce the surface temperature characteristics of the present climate in China, whereas the WRF tends to underestimate the surface temperature over most of China. Both the SDSM and WRF require further work to improve their ability to downscale precipitation. Both statistical and dynamical downscaling methods produce future surface temperatures for 2041–2060 that are markedly different from the historical climatology. However, the changes in projected precipitation differ between the two downscaling methods. Indeed, large uncertainties remain in terms of the direction and magnitude of future precipitation changes over China.

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“…This study used the MYNN scheme for the PBL processes. The Noah scheme (Chen and Dudhia, 2001) and the Rapid Radiative Transfer Model for GCMs (RRTMG) scheme (Mlawer et al, 1997;Iacono et al, 2000) were implemented, respectively, for the land surface and radiative transfer processes.…”

Section: Introductionmentioning

confidence: 99%

Modeling extreme precipitation over East China with a global variable-resolution modeling framework (MPASv5.2): impacts of resolution and physics

Zhao

Wang

et al. 2019

Geosci. Model Dev.

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Abstract. The non-hydrostatic atmospheric Model for Prediction Across Scales (MPAS-A), a global variable-resolution modeling framework, is applied at a range of resolutions from hydrostatic (60, 30, 16 km) to non-hydrostatic (4 km) scales using regional refinement over East Asia to simulate an extreme precipitation event. The event is triggered by a typical wind shear in the lower layer of the Meiyu front in East China on 25–27 June 2012 during the East Asian summer monsoon season. The simulations are evaluated using ground observations and reanalysis data. The simulated distribution and intensity of precipitation are analyzed to investigate the sensitivity to model configuration, resolution, and physics parameterizations. In general, simulations using global uniform-resolution and variable-resolution meshes share similar characteristics of precipitation and wind in the refined region with comparable horizontal resolution. Further experiments at multiple resolutions reveal the significant impacts of horizontal resolution on simulating the distribution and intensity of precipitation and updrafts. More specifically, simulations at coarser resolutions shift the zonal distribution of the rain belt and produce weaker heavy precipitation centers that are misplaced relative to the observed locations. In comparison, simulations employing 4 km cell spacing produce more realistic features of precipitation and wind. The difference among experiments in modeling rain belt features is mainly due to the difference in simulated wind shear formation and evolution during this event. Sensitivity experiments show that cloud microphysics have significant effects on modeling precipitation at non-hydrostatic scales, but their impacts are relatively small compared to that of convective parameterizations for simulations at hydrostatic scales. This study provides the first evidence supporting the use of convection-permitting global variable-resolution simulations for studying and improving forecasting of extreme precipitation over East China and motivates the need for a more systematic study of heavy precipitation events and the impacts of physics parameterizations and topography in the future. The key points are as follows. Model for Prediction Across Scales (MPAS) simulations at global uniform and variable resolutions share similar characteristics of precipitation and wind in the refined region. Numerical experiments reveal significant impacts of resolution on simulating the distribution and intensity of precipitation and updrafts. This study provides evidence supporting the use of convection-permitting global variable-resolution simulation to study extreme precipitation.

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Sensitivity of simulated extreme precipitation and temperature to convective parameterization using RegCM3 in China

Cited by 12 publications

References 66 publications

Evaluation of the performance of non-hydrostatic RegCM4 (RegCM4-NH) over China

Evaluation of the performance of non-hydrostatic RegCM4 (RegCM4-NH) over China

Statistical downscaling and dynamical downscaling of regional climate in China: Present climate evaluations and future climate projections

Modeling extreme precipitation over East China with a global variable-resolution modeling framework (MPASv5.2): impacts of resolution and physics

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