• Journal of Korean Society for Atmospheric Environment
• /
• v.32 no.4
• /
• pp.372-383
• /
• 2016

This study aimed at analyzing the sensitivity of ozone simulation in accordance with the meteorological nudging for a high nocturnal ozone episode. To demonstrate the effectiveness of nudging methods (e.g., nudging techniques and application domains), the following six experiments were designed: (1) control without nudging, (2) experiment with application of observation nudging to all domains (domain 1~4), and (3)~(6) experiments with application of grid nudging to domain 1, domain 1~2, domain 1~3 and all domains, respectively. As a result, the meteorological nudging had a direct (improvement of input data) and indirect (estimate natural emission) effect on ozone simulation. Nudging effects during the daytime were greater than those during the nighttime due to low accuracy of wind direction during the nighttime. On comparison of the nudging techniques, the experiments in which grid nudging was applied showed more improved results than the experiments in which observation nudging was applied. At this time point, the simulated concentrations were generally similar to the observed concentrations due to the increase in the nudging effect when grid nudging was applied up to the sub-domain. However, for high nocturnal ozone uptakes, the experiment in which grid nudging was applied do domain 1~3 showed better results than the other experiments. This is because, when grid nudging was applied to the high resolution domain (e.g., domain 4 with 1 km), the local characteristics were removed due to the smoothing effects of meteorological conditions.

• Journal of Environmental Science International
• /
• v.25 no.5
• /
• pp.683-694
• /
• 2016

Sensitivity analysis of the WRF model according to the impact of nudging (e.g., nudging techniques and application domains) was conducted during high nocturnal ozone episode to improve the prediction of the regional ozone concentration in the southeastern coastal area of the Korean peninsula. The analysis was performed by six simulation experiments: (1) without nudging (e.g., CNTL case), (2) with observation nudging (ONE case) to all domains (domain 1~4), (3) with grid nudging (GNE case) to all domains, (4)~(6) with grid nudging to domain 1, domain 1~2 and domain 1~3, respectively (GNE-1, GNE-2, GNE-3 case). The results for nudging techniques showed that the GNE case was in very good agreement with those observed during all analysis periods (e.g., daytime, nighttime, and total), as compared to the ONE case. In particular, the large effect of grid nudging on the near-surface meteorological factors (temperature, relative humidity, and wind fields) was predicted at the coastline and nearby sea during daytime. The results for application domains showed that the effects of nudging were distinguished between the meteorological factors and between the time periods. When applied grid nudging until subdomain, the improvement effects of temperature and relative humidity had differential tendencies. Temperature was increased for all time, but relative humidity was increased in daytime and was decreased in nighttime. Thus, GNE case showed better result than other cases.

• Journal of Korean Society for Atmospheric Environment
• /
• v.31 no.1
• /
• pp.1-14
• /
• 2015

This study investigates the impact of enhanced regional meteorological fields on improvement of wind energy forecasting accuracy in the southwestern coast of the Korean Peninsula. To clarify the effect of detailed surface boundary data and application of analysis nudging technique on simulated meteorological fields, several WRF simulations were carried out. Case_LT, which is a simulation with high resolution terrain height and land use data, shows the most remarkable accuracy improvement along the shoreline mainly due to modified surface characteristics such as albedo, roughness length and thermal inertia. Case_RS with high resolution SST data shows accurate SST distributions compared to observation data, and they led to change in land and sea breeze circulation. Case_GN, grid nudging applied simulation, also shows changed temperature and wind fields. Especially, the application of grid nudging dominantly influences on the change of horizontal wind components in comparison with vertical wind component.

• Journal of Environmental Science International
• /
• v.27 no.11
• /
• pp.1141-1154
• /
• 2018

Numerical experiments were carried out to investigate the effect of data assimilation of observational data on weather and PM (particulate matter) prediction. Observational data applied to numerical experiment are aircraft observation, satellite observation, upper level observation, and AWS (automatic weather system) data. In the case of grid nudging, the prediction performance of the meteorological field is largely improved compared with the case without data assimilations because the overall pressure distribution can be changed. So grid nudging effect can be significant when synoptic weather pattern strongly affects Korean Peninsula. Predictability of meteorological factors can be expected to improve through a number of observational data assimilation, but data assimilation by single data often occurred to be less predictive than without data assimilation. Variation of air pressure due to observation nudging with high prediction efficiency can improve prediction accuracy of whole model domain. However, in areas with complex terrain such as the eastern part of the Korean peninsula, the improvement due to grid nudging were only limited. In such cases, it would be more effective to aggregate assimilated data.

• Journal of Environmental Science International
• /
• v.29 no.1
• /
• pp.33-44
• /
• 2020

Recently, a variety of modeling studies have been conducted to examine the air quality over South Korea during the Korea - United States Air Quality (KORUS-AQ) campaign period (May 1 to June 10, 2016). This study investigates the impact of different meteorological initializations on atmospheric modeling results. We conduct several simulations during the KORUS-AQ period using the Weather Research and Forecasting (WRF) model with two different initial datasets, which is FNL of NCEP and ERA5 of ECMWF. Comparing the raw initial data, ERA5 showed better accuracy in the temperature, wind speed, and mixing ratio fields than those of NCEP-FNL. On the other hand, the results of WRF simulations with ERA5 showed better accuracy in the simulated temperature and mixing ratio than those with FNL, except for wind speed. Comparing the nudging efficiency of temperature and wind speed fields, the grid nudging effect on the FNL simulation was larger than that on the ERA5 simulation, but the results of mixing ratio field was the opposite. Overall, WRF simulation with ERA5 data showed a better performance for temperature and mixing ratio simulations than that with FNL data. For wind speed simulation, however, WRF simulation with FNL data indicated more accurate results compared to that with ERA5 data.

• Journal of Environmental Science International
• /
• v.26 no.12
• /
• pp.1307-1319
• /
• 2017

In this study, we investigated the impact of different initial data on atmospheric modeling results using the Weather Research and Forecast (WRF) model. Four WRF simulations were conducted with different initialization in March 2015, which showed the highest monthly mean $PM_{10}$ concentration in the recent ten years (2006-2015). The results of WRF simulations using NCEP-FNL and ERA-Interim were compared with observed surface temperature and wind speed data, and the difference of grid nudging effect on WRF simulation between the two data were also analyzed. The FNL simulation showed better accuracy in the simulated temperature and wind speed than the Interim simulation, and the difference was clear in the coastal area. The grid nudging effect on the Interim simulation was larger than that of the FNL simulation. Despite of the higher spatial resolution of ERA-Interim data compared to NCEP-FNL data, the Interim simulation showed slightly worse accuracy than those of the FNL simulation. It was due to uncertainties associated with the Sea Surface Temperature (SST) field in the ERA-Interim data. The results from the Interim simulation with different SST data showed significantly improved accuracy than the standard Interim simulation. It means that the SST field in the ERA-Interim data need to be optimized for the better WRF simulation. In conclusion, although the WRF simulation with ERA-Interim data does not show reasonable accuracy compared to those with NCEP-FNL data, it would be able to be Improved by optimizing the SST variable.

• Journal of the korean society of oceanography
• /
• v.39 no.1
• /
• pp.72-95
• /
• 2004

The Yellow Sea is characterized by relatively shallow water depth, varying range of tidal action and very complex coastal geometry such as islands, bays, peninsulas, tidal flats, shoals etc. The dynamic system is controlled by tides, regional winds, river discharge, and interaction with the Kuroshio. The circulation, water mass properties and their variability in the Yellow Sea are very complicated and still far from clear understanding. In this study, an effort to improve our understanding the dynamic feature of the Yellow Sea system was conducted using numerical simulation with the ROMS model, applying climatologic forcing such as winds, heat flux and fresh water precipitation. The inter-annual variability of general circulation and thermohaline structure throughout the year has been obtained, which has been compared with observational data sets. The simulated horizontal distribution and vertical cross-sectional structures of temperature and salinity show a good agreement with the observational data indicating significantly the water masses such as Yellow Sea Warm Water, Yellow Sea Bottom Cold Water, Changjiang River Diluted Water and other sporadically observed coastal waters around the Yellow Sea. The tidal effects on circulation and dynamic features such as coastal tidal fronts and coastal mixing are predominant in the Yellow Sea. Hence the tidal effects on those dynamic features are dealt in the accompanying paper (Kim et at., 2004). The ROMS model adopts curvilinear grid with horizontal resolution of 35 km and 20 vertical grid spacing confirming to relatively realistic bottom topography. The model was initialized with the LEVITUS climatologic data and forced by the monthly mean air-sea fluxes of momentum, heat and fresh water derived from COADS. On the open boundaries, climatological temperature and salinity are nudged every 20 days for data assimilation to stabilize the modeling implementation. This study demonstrates a Yellow Sea version of Atlantic Basin experiment conducted by Haidvogel et al. (2000) experiment that the ROMS simulates the dynamic variability of temperature, salinity, and velocity fields in the ocean. However the present study has been improved to deal with the large river system, open boundary nudging process and further with combination of the tidal forcing that is a significant feature in the Yellow Sea.

• Atmosphere
• /
• v.30 no.3
• /
• pp.257-276
• /
• 2020

Faithful evaluation of the meteorological input is a prerequisite for a better understanding of air quality model performance. Despite the importance, the preliminary meteorological assessment has rarely been concerned. In this study, we aim to evaluate the performance of the Weather Research and Forecasting (WRF) model conducting a year-long high-resolution meteorological simulation in 2016 over the Seoul metropolitan area. The WRF model was configured based on a series of sensitivity simulations of initial/boundary meteorological conditions, land use mapping data, reanalysis grid nudging method, domain nesting method, and urban canopy model. The simulated results of winds, air temperature, and specific humidity in the atmospheric boundary layer (ABL) were evaluated following statistical evaluation guidance using the surface and upper meteorological measurements. The statistical evaluation results are presented. The model performance was interpreted acceptable for air quality modeling within the statistical criteria of complex conditions, showing consistent overestimation in wind speeds. Further statistical analysis showed that the meteorological model biases were highly systematic with systematic bias fractions (f_SB) of 20~50%. This study suggests that both the momentum exchange process of the surface layer and the ABL entrainment process should be investigated for further improvement of the model performance.