A Numerical Study of Mountain-Plain Breeze Circulation in Eastern Chengdu, China

Tian, Ye; Miao, Jianjun

doi:10.3390/su11102821

Cited by 12 publications

(6 citation statements)

References 38 publications

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“…The average 98th percentile wind gust in the coastal areas is 10.6 m/s, which is 10% higher than the wind gust in the noncoastal area (9.5 m/s). This result is consistent with [6,7] stated that the sea-land and mountain-valley systems significantly affect the wind system. Further, this study showed the consistency of the higher wind gust speed of sea-land breeze compared to mountain valley wind gust speed.…”

Section: The 98 Th -Percentile and 50-year Return Level Wind Gust Speedsupporting

confidence: 92%

An Overview of Extreme Storm Trends in Java Island using Storm Severity Index (SSI)

Susandi

Pratama

Wijaya

2023

IOP Conf. Ser.: Earth Environ. Sci.

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Extreme winds can lead to extreme storms, which are among the most frequent forms of extreme weather in Indonesia. With climate change predicted to increase the adverse impact of extreme weather, it is crucial to keep track of and gauge the severity of storm events. Storm Severity Index (SSI) can be used to measure the severity of storms, which is defined by their intensity, duration, and extent. SSI has been used in continental areas. However, the application of SSI in the maritime continent is still limited. This study explores the application of SSI to measure extreme storms in Indonesia based on wind gust speed. This study uses wind gust data in 1959-2021 from ERA5 reanalysis data and calculates the SSI based on the 98th percentile and the 50-year return value of the wind data. This study also explores the meteorological events that coincide with high SSI values. This study found the SSI able to capture high wind gust events in Java Island. This study finds high SSI value coincides with tropical cyclone events in the Indian Ocean. Topography affects the area on Java Island that has a high SSI value. Further study should evaluate the impact of the coastal and non-coastal areas to reduce the significant effect of sea-land breeze or mountain-valley breeze. In addition, future research also needs to address the significance level of the duration of events in a severe storm to enhance the information on severity.

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Section: The 98 Th -Percentile and 50-year Return Level Wind Gust Speedsupporting

confidence: 92%

An Overview of Extreme Storm Trends in Java Island using Storm Severity Index (SSI)

Susandi

Pratama

Wijaya

2023

IOP Conf. Ser.: Earth Environ. Sci.

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“…The WRF is a globally used NWP model for analyzing atmospheric processes and extreme weather conditions such as cold waves, heat waves, and precipitation [32]. Tian and Miao (2019) simulated mountain plain breeze circulation using BouLac PBL (planetary boundary layer), Noah + UCM land surface, and MM5 surface layer schemes in the WRF model in eastern Chengdu, China [33]. Mohan and Gupta (2018); Gunwani and Mohan (2017); Sathyanadh, Prabha et al (2017) simulated the meteorological variables using the number of physical WRF schemes in various parts of India to boost the WRF results [34][35][36].…”

Section: Introductionmentioning

confidence: 99%

Evaluation the WRF Model with Different Land Surface Schemes: Heat Wave Event Simulations and Its Relation to Pacific Variability over Coastal Region, Karachi, Pakistan

et al. 2021

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This study investigates the relative role of land surface schemes (LSS) in the Weather Research and Forecasting (WRF) model, Version 4, to simulate the heat wave events in Karachi, Pakistan during 16–23 May 2018. The efficiency of the WRF model was evaluated in forecasting heat wave events over Karachi using the three different LSS, namely NOAH, NOAH-MP, and RUC. In addition to this we have used the longwave (RRTM) and shortwave (Dudhia) in all schemes. Three simulating setups were designed with a combination of shortwave, longwave, and LSS: E1 (Dudhia, RRTM, and Noah), E2 (Dudhia, RRTM, and Noah-MP), and E3 (Dudhia, RRTM, and RUC). All setups were carried out with a finer resolution of 1 km × 1 km. Findings of current study depicted that E2 produces a more realistic simulation of daily maximum temperature T(max) at 2 m, sensible heat (SH), and latent heat (LH) because it has higher R2 and lower errors (BIAS, RMSE, MAE) compared to other schemes. Consequently, Noah-MP (LSS) accurately estimates T(max) and land surface heat fluxes (SH&LH) because uses multiple physics options for land atmosphere interaction processes. According to statistical analyses, E2 setup outperforms other setups in term of T(max) and (LH&SH) forecasting with the higher Nash-Sutcliffe efficiency (NSE) agreement is 0.84 (0.89). This research emphasizes that the selection of LSS is of vital importance in the best simulation of T(max) and SH (LH) over Karachi. Further, it is resulted that the SH flux is taking a higher part to trigger the heat wave event intensity during May 2018 due to dense urban canopy and less vegetated area. El Niño-Southern Oscillation (ENSO) event played role to prolong and strengthen the heat wave period by effecting the Indian Ocean Dipole (IOD) through walker circulation extension.

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“…On the one hand, the Noah LSM is one of the most widely used land surface schemes for research studies, as well as for weather and regional climate modeling [24]. In this regard, Noah LSM has not only been coupled to the WRF model but also to the operational North American Mesoscale (NAM) Forecast System, the Global Forecast System (GFS), and other National Centers for Environmental Prediction (NCEP) modeling systems [19,25,26]. On the other hand, the Noah-MP model is an evolutional version of the original Noah LSM.…”

Section: Introductionmentioning

confidence: 99%

Impact of Noah-LSM Parameterizations on WRF Mesoscale Simulations: Case Study of Prevailing Summer Atmospheric Conditions over a Typical Semi-Arid Region in Eastern Spain

et al. 2021

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The current study evaluates the ability of the Weather Research and Forecasting Model (WRF) to forecast surface energy fluxes over a region in Eastern Spain. Focusing on the sensitivity of the model to Land Surface Model (LSM) parameterizations, we compare the simulations provided by the original Noah LSM and the Noah LSM with multiple physics options (Noah-MP). Furthermore, we assess the WRF sensitivity to different Noah-MP physics schemes, namely the calculation of canopy stomatal resistance (OPT_CRS), the soil moisture factor for stomatal resistance (OPT_BTR), and the surface layer drag coefficient (OPT_SFC). It has been found that these physics options strongly affect the energy partitioning at the land surface in short-time scale simulations. Aside from in situ observations, we use the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor to assess the Land Surface Temperature (LST) field simulated by WRF. Regarding multiple options in Noah-MP, WRF has been configured using three distinct soil moisture factors to control stomatal resistance (β factor) available in Noah-MP (Noah, CLM, and SSiB-types), two canopy stomatal resistance (Ball–Berry and Jarvis), and two options for surface layer drag coefficients (Monin–Obukhov and Chen97 scheme). Considering the β factor schemes, CLM and SSiB-type β factors simulate very low values of the latent heat flux while increasing the sensible heat flux. This result has been obtained independently of the canopy stomatal resistance scheme used. Additionally, the surface skin temperature simulated by Noah-MP is colder than that obtained by the original Noah LSM. This result is also highlighted when the simulated surface skin temperature is compared to the MSG-SEVIRI LST product. The largest differences between the satellite data and the mesoscale simulations are produced using the Noah-MP configurations run with the Monin–Obukhov parameterization for surface layer drag coefficients. In contrast, the Chen97 scheme shows larger surface skin temperatures than Monin–Obukhov, but at the expense of a decrease in the simulated sensible heat fluxes. In this regard, the ground heat flux and the net radiation play a key role in the simulation results.

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A Numerical Study of Mountain-Plain Breeze Circulation in Eastern Chengdu, China

Cited by 12 publications

References 38 publications

An Overview of Extreme Storm Trends in Java Island using Storm Severity Index (SSI)

An Overview of Extreme Storm Trends in Java Island using Storm Severity Index (SSI)

Evaluation the WRF Model with Different Land Surface Schemes: Heat Wave Event Simulations and Its Relation to Pacific Variability over Coastal Region, Karachi, Pakistan

Impact of Noah-LSM Parameterizations on WRF Mesoscale Simulations: Case Study of Prevailing Summer Atmospheric Conditions over a Typical Semi-Arid Region in Eastern Spain

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