• Atmosphere
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• v.34 no.1
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• pp.23-34
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• 2024

The Korea Meteorological Administration has improved medium-range weather forecasts by implementing post-processing methods to minimize numerical model errors. In this study, we employ a statistical correction technique known as the minimum continuous ranked probability score (CRPS) to refine medium-range forecast guidance. This technique quantifies the similarity between the predicted values and the observed cumulative distribution function of the Unified Model Ensemble Prediction System for Global (UM EPSG). We evaluated the performance of the medium-range forecast guidance for surface air temperature and relative humidity, noting significant enhancements in seasonal bias and root mean squared error compared to observations. Notably, compared to the existing the medium-range forecast guidance, temperature forecasts exhibit 17.5% improvement in summer and 21.5% improvement in winter. Humidity forecasts also show 12% improvement in summer and 23% improvement in winter. The results indicate that utilizing the minimum CRPS for medium-range forecast guidance provide more reliable and improved performance than UM EPSG.

• Atmosphere
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• v.17 no.1
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• pp.17-26
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• 2007

The station relocations, the replacement of instruments, and the change of a procedure for calculating derived climatic quantities from observations are well-known nonclimatic factors that seriously contaminate the worthwhile results in climate study. Prior to embarking on the climatological analysis, therefore, the quality and homogeneity of the utilized data sets should be properly evaluated with metadata. According to the metadata of the Korea Meteorological Administration (KMA), there have been plenty of changes in the procedure computing the daily mean values of temperature, humidity, etc, since 1904. For routine climatological work, it is customary to compute approximate daily mean values for individual days from values observed at fixed hours. In the KMA, fixed hours were totally 5 times changed: at four-hourly, four-hourly interval with additional 12 hour, eight-hourly, six-hourly, three-hourly intervals. In this paper, the homogeneity in the daily mean temperature dataset of the KMA was assessed with the consistency and efficiency of point estimators. We used the daily mean calculated from the 24 hourly readings as a potential true value. Approximate daily means computed from temperatures observed at different fixed hours have statistically different properties. So this inhomogeneity in KMA climate data should be kept in mind if you want to analysis secular aspects of Korea climate using this data set.

• Atmosphere
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• v.16 no.3
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• pp.235-246
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• 2006

Remote sensing techniques using satellites or the scanning weather radars depend mostly on the presence of clouds or precipitation, and leave the extensive regions of clear air unobserved. But wind profilers provide the most direct measurements of mesoscale vertical air motion in the troposphere, even in the context of heavy precipitation. In this paper, the precipitation events during the Changma period was classified into 4 precipitation types - stratiform, mixed stratiform/ convective, deep convective, and shallow convective. The parameters for the classification of analysis are the vertical structure of reflectivity, Doppler velocity, and spectral width measured with the wind profiler at Haenam for a three-year period (2003-2005). In addition, the synoptic fields and total amount of precipitation were analyzed using the Global Final Analyses (FNL) data and the Global Precipitation Climatology Project (GPCP) data. During the Changma period, the results show that the stratiform type was dominant under the moist-neutral atmosphere in 2003, whereas the deep convective type was under the moist unstable condition in 2004. The stratiform type was no less popular than the deep convective type among four seasons because the moist neutral layer was formed by the convergence between the upper-level jet and the low-level jet, and by the moisture transport along the western rim of the North Pacific subtropical anticyclone.

• Journal of the Korean earth science society
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• v.28 no.5
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• pp.545-555
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• 2007

Ocean general circulation model developed by GFDL on the basis of MOM4 of FMS are examined and evaluated in order to elucidate the global ocean status. The model employs a tripolar grid system to resolve the Arctic Ocean without polar filtering. The meridional resolution gradually increases from $1/3^{\circ}$ at the equator to $1^{\circ}$ at $30^{\circ}N(S)$. Other horizontal grids have the constant $1^{\circ}$ and vertical grids with 50 levels. The ocean is also coupled to the GFDL sea ice model. It considers tidal effects along with fresh water and chlorophyll concentration. This model is integrated for a 100 year duration with 96 cpu forced by German OMIP and CORE dataset. Levitus, WOA01 climatology, serial CTD observations, WOCE and Argo data are all used for model validation. General features of the world ocean circulation are well simulated except for the western boundary and coastal region where strong advection or fresh water flux are dominant. However, we can find that information concerning chlorophyll and sea ice, newly applied to MOM4 as surface boundary condition, can be used to reduce a model bias near the equatorial and North Pacific ocean.

• Journal of the Korean earth science society
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• v.42 no.4
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• pp.390-400
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• 2021

Ocean biogeochemistry plays a crucial role in sustaining the marine ecosystem and global carbon cycle. To investigate the oceanic biogeochemical responses to iron parameters in the tropical Pacific, we conducted sensitivity experiments using the Nucleus for European Modelling of the Ocean-Tracers of Ocean Phytoplankton with Allometric Zooplankton (NEMO-TOPAZ) model. Compared to observations, the NEMO-TOPAZ model overestimated the concentrations of chlorophyll and dissolved iron (DFe). The sensitivity tests showed that with increasing (+50%) iron scavenging rates, chlorophyll concentrations in the tropical Pacific were reduced by approximately 16%. The bias in DFe also decreased by approximately 7%; however, the sea surface temperature was not affected. As such, these results can facilitate the development of the model tuning strategy to improve ocean biogeochemical performance using the NEMO-TOPAZ model.

• Journal of Environmental Science International
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• v.27 no.11
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• pp.1141-1154
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• 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
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• v.33 no.6
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• pp.435-442
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• 2024

We investigated the accuracy of surface air temperature prediction according to the selection of land-use data and initial meteorological data using the Weather Research and Forecasting model-v4.2.1. A numerical experiment was conducted at the Daegu Dyeing Industrial Complex. We initially used meteorological input data from GFS (Global forecast system)and GDAPS (Global data assimilation and prediction system). High-resolution input data were generated and used as input data for the weather model using the land cover data of the Ministry of Environment and the digital elevation model of the Ministry of Land, Infrastructure, and Transport. The experiment was conducted by classifying the terrestrial and topographic data (land cover data) and meteorological data applied to the model. For simulations using high-resolution terrestrial data(10 m), global data assimilation, and prediction system data(CASE 3), the calculated surface temperature was much closer to the automatic weather station observations than for simulations using low-resolution terrestrial data(900 m) and GFS(CASE 1).

• Journal of Korea Water Resources Association
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• v.45 no.8
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• pp.755-765
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• 2012

The Land Surface Temperature (LST) is one of the significant factors to understand the water and energy cycles between the land surface and atmosphere. However, few previous studies for spatio-temporal variations of LST has been investigated. In this study, we conducted comparative analyses between the Communication, Ocean and Meteorological Satellite (COMS) and MOderate-Resolution Imaging Spectroradiometer (MODIS) LST data. We compared COMS data with observations to identify the accuracy and found relative underestimated patterns of the COMS data as compared to observations. We also found that COMS LST were underestimated in compare to MODIS LST. The Terra LST was verified to have more similar trends with the COMS LST rather than Aqua LST. While we identified the applicability of COMS based on the results of similar tendencies of two comparisons, more intensive validation research at a variety of field conditions should be conducted to gurantee current COMS LST.

• Journal of Environmental Science International
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• v.16 no.4
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• pp.399-407
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• 2007

The characteristics of meteorological conditions relevant to Asian dust (AD) outbreaks and their occurrence frequencies were analyzed in four source regions (R1 to R4) during spring months (March to May) of 1995-2002. Moreover, the concentration variations of AD (e.g., $PM_{10}$) observed in Korea were investigated during the study period. In the relationship between AD outbreaks and three meteorological parameters (i.e., air temperature, wind speed, and aridity), the largest AD outbreaks in April (${\sim}250$ observations) mostly occurred in R2 when air temperature ranging from 10.0 to $15^{\circ}C$ and surface wind speed from 7 to $9m\;s^{-1}$ were recorded. Moreover, the aridity ($\geq4$) in April was significantly high in R2 with the maximum frequency of AD outbreaks (i.e., 206 observations). On the other hand, the number (percentage) of days belonging to AD events observed in five Korean cities were found to be 116 (44%), 121 (46%), and 26 days (10%) in March, April, and May, respectively. The mean $PM_{10}$ concentrations were found to range from 150 to 220, 150 to 200, and 95 to $120{\mu}g\;m^{-3}$ in March, April, and May, respectively. Consequently, this implied that the AD events in Korea were found to be gradually frequent in early spring and to be affected from the large AD outbreaks observed in the source regions.

• Journal of the Korean earth science society
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• v.40 no.4
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• pp.406-413
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• 2019

Red-Green-Blue (RGB) imagery techniques are useful for both forecasters and public users because they are intuitively understood, have advantageous visualization, and do not lose observational information. This study presents a novel RGB convective cloud product and its application to tropical cyclone analysis using Communication, Oceanography, and Meteorology (COMS) satellite observations. The RGB convective cloud product was developed using the brightness temperature differences between WV ($6.75{\mu}m$) and IR1 ($10.8{\mu}m$), and IR2 ($12.0{\mu}m$) and IR1 ($10.8{\mu}m$) as well as the brightness temperature in the IR1 bands of the COMS, with the threshold values estimated from the Korea Meteorological Administration (KMA) radar observations and the EUMETSAT RGB recipe. To verify the accuracy of the convective cloud RGB product, the product was applied to the center positions analysis of two typhoons in 2013. Thus, the convective cloud RGB product threshold values were estimated for WV-IR1 (-20 K to 15 K), IR1 (210 K to 300 K), and IR1-IR2 (-4 K to 2 K). The product application in typhoon analysis shows relatively low bias and root mean square errors (RMSE)s of 23 and 28 km for DANAS in 2013, and 17 and 22 km for FRANCISCO in 2013, as compared to the best tracks data from the Regional Specialized Meteorological Center (RSMC) in Tokyo. Consequently, our proposed RGB convective cloud product has the advantages of high accuracy and excellent visualization for a variety of meteorological applications.