• Atmosphere
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• v.30 no.2
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• pp.169-181
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• 2020

We conducted a study on the impact of observation station density; this was done in order to enable the accurate estimation of spatial meteorological variables. The purpose of this study is to help operate an efficient observation network by examining distributions of temperature, relative humidity, and wind speed in a test area of a three-dimensional meteorological observation project in the Yeongdong region in 2019. For our analysis, we grouped the observation stations as follows: 41 stations (for Step 4), 34 stations (for Step 3), 17 stations (for Step 2), and 10 stations (for Step 1). Grid values were interpolated using the kriging method. We compared the spatial accuracy of the estimated meteorological grid by using station density. The effect of increased observation network density varied and was dependent on meteorological variables and weather conditions. The temperature is sufficient for the current weather observation network (featuring an average distance about 9.30 km between stations), and the relative humidity is sufficient when the average distance between stations is about 5.04 km. However, it is recommended that all observation networks, with an average distance of approximately 4.59 km between stations, be utilized for monitoring wind speed. In addition, this also enables the operation of an effective observation network through the classification of outliers.

• Atmosphere
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• v.26 no.1
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• pp.59-72
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• 2016

The comparison of prediction errors in geopotential height, temperature, and precipitation forecasts is made quantitatively to evaluate medium-range forecast skills between Global Seasonal Forecasting System version 5 (GloSea5) and Unified Model (UM) in operation by Korea Meteorological Administration during 2014. In addition, the performances in prediction of sea surface temperature anomaly in NINO3.4 region, Madden and Julian Oscillation (MJO) index, and tropical storms in western north Pacific are evaluated. The result of evaluations appears that the forecast skill of UM with lower values of root-mean square error is generally superior to GloSea5 during forecast periods (0 to 12 days). The forecast error tends to increase rapidly in GloSea5 during the first half of the forecast period, and then it shows down so that the skill difference between UM and GloSea5 becomes negligible as the forecast time increases. Precipitation forecast of GloSea5 is not as bad as expected and the skill is comparable to that of UM during 10-day forecasts. Especially, in predictions of sea surface temperature in NINO3.4 region, MJO index, and tropical storms in western Pacific, GloSea5 shows similar or better performance than UM. Throughout comparison of forecast skills for main meteorological elements and weather extremes during medium-range, the effects of initial and model errors in atmosphere-ocean coupled model are verified and it is suggested that GloSea5 is useful system for not only seasonal forecasts but also short- and medium-range forecasts.

• Atmosphere
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• v.14 no.1
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• pp.4-23
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• 2004

To monitor the world's oceans and understand the role of the oceans for climate change, an Array for Real-time Geostrophic Oceanography (ARGO) program has been carried out since year 2000. Autonomous profiling floats of about 820 are reporting the vertical temperature, salinity, and pressure profiles of the upper 2000 m underwater at regular time intervals. Meteorological Research Institute (METRI) of Korea Meteorological Administration (KMA) launched 45 floats at the East Sea and the western Pacific to understand characteristics of water properties and develop the global ocean observation system as a part of international cooperation project. In this study, we introduce ARGO program, METRI-ARGO and the features of APEX float itself and their data formats. We also describe the significant points to be considered for using ARGO data.

• Atmosphere
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• v.17 no.1
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• pp.101-108
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• 2007

To observe and analyze the cloud and fog characteristics, the METeorological Research Institute (METRI) has established the Cloud Physics Observation System (CPOS) by implementing the cloud observation instruments: Forward Scattering Spectrometer Probe (FSSP), PARticle SIze and VELocity (PARSIVEL), Microwave Radiometer (MWR), Micro Rain Radar (MRR), and 3D-AWS at the Daegwallyeong Enhanced Mountain Weather Observation Center. The cloud-related products of CPOS and the validation status for the size distribution of FSSP, the precipitable water of MWR, and the rainfall rate of MRR and PARSIVEL are described.

• Atmosphere
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• v.17 no.1
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• pp.27-44
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• 2007

The purpose of this study is to investigate predictability of the seasonal simulation by the METRI (Meteorological Research Institute) AGCM (Atmospheric General Circulation Model), which is a long-term prediction model for the METRI 3-month prediction system. We examine the performance skill of climate simulation and predictability by the analysis of variance of the METRI AGCM, focusing on the precipitation, 850 hPa temperature, and 500 hPa geopotential height. According to the result, the METRI AGCM shows systematic errors with seasonal march, and represents large errors over the equatorial region, compared to the observation. Also, the response of the METRI AGCM by the variation of the sea surface temperature is obvious for the wintertime and springtime. However, the METRI AGCM does not show the significant ENSO-related signal in autumn. In case of prediction over the east Asian region, errors between the prediction results and the observation are not quite large with the lead-time. However, in the predictability assessment using the analysis of variance method, longer lead-time makes the prediction better, and the predictability becomes better in the springtime.

• Atmosphere
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• v.17 no.1
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• pp.45-53
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• 2007

In order to investigate the impacts of heat wave on human health, cluster analysis of meteorological elements (e.g., temperature, dewpoint, sea level pressure, visibility, cloud amount, and wind components) for identifying offensive synoptic air masses is employed. Meteorological data at Seoul during the past 30 years are used. The daily death data at Seoul are also employed. Occurrence frequency of heat waves which is defined by daily maximum temperature greater than the threshold temperature (i.e., $31.2^{\circ}C$) was analyzed. The result shows that the frequency and duration of heat waves at Seoul are increasing during the past 30 years. In addition, the increasing trend of the frequency and duration clearly appears in late spring and early autumn as well as summer. Factor analysis shows that 65.1% of the total variance can be explained by 4 components which are linearly independent. Eight clusters (or synoptic air masses) were classified and found to be optimal for representing the summertime air masses at Seoul, Korea. The results exhibit that cluster-mean values of meteorological variables of an offensive air mass (or cluster) are closely correlated with the observed and standardized deaths.

• Journal of Environmental Science International
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• v.21 no.4
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• pp.461-470
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• 2012

Agriculture is more influenced by environmental factors rather than other industries. Among the environmental factors, the meteorological conditions mainly impact the output of agricultural products. Hence, the purpose of this study is to analyze the impact of meteorological factors on the output of elemental agricultural products. As a first step, we obtained the data of the meteorological factors (i.e., precipitation, humidity, temperature, insolation, snowdrifts, wind velocity) and the output of the various agricultural products (i.e., grain, fruits and vegetables, root crops, green vegetables, seasoned vegetables, fruits, special crops) from the year 1990 to 2009 (20 years) of Seoul and the six metropolitan cities in Korea. Then, the analysis of the correlation between the agricultural product with the largest output and the meteorological factors of the place where the corresponding agricultural product is most produced, was carried out in order to determine the core meteorological factor that most impacts the output of agricultural product. The correlation analysis revealed that humidity, insolation and wind velocity have been the crucial meteorological factors to influence the output of the agricultural products. From the result, we can induce that the meteorological forecast information about the vital meteorological factors, i.e., humidity, insolation and wind velocity, facilitates the optimized cultivation plan to maximize the output of agricultural products.

• Atmosphere
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• v.16 no.4
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• pp.269-278
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• 2006

Extremely hot weathers may cause major weather-related deaths in the summertime. Influences of heat waves on daily mortalities in 6 major cities of South Korea were investigated. Daily deaths at Seoul were exponentially increased with the daily maximum temperature. However, there were regional differences of the temperature dependence on the mortality because of an acclimation effect of inhabitants. The threshold temperature (with respect to daily maximum temperature) at Seoul was found to be about $31^{\circ}C$ provided that it is determined by a two-phase regression model. The meteorological causes of recordable hot summer in late July of 1994 and their impacts on human health were also investigated. Strong surface heating caused by strong insolation under conditions with clear sky and dry surface due to prolonged drought was likely to be closely associated with the extreme hot weather in 1994 in South Korea.

• Atmosphere
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• v.16 no.3
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• pp.215-223
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• 2006

Among observational, local-environmental, and large-scale factors causing significant changes in climate records, the site relocations and the replacement of the instruments are well-known nonclimatic factors for the analysis of climatic trends, climatic variability, and for the detection of anthropogenic climate change such as heat-island effect and global warming. Using dataset that were contaminated by these nonclimatic factors can affect seriously the assessment of climatic trends and variability, and the detection of the climatic change signal. In this paper, the inhomogeneities, which have been caused by relocation of the observation site, in the climate data of Korea Meteorological Administration (KMA) were examined using two-phase regression model. The observations of pan evaporation and wind speed are more sensitive to site relocations than those of other meteorological elements, such as daily mean, maximum and minimum temperatures, with regardless to region.

• Atmosphere
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• v.26 no.1
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• pp.185-192
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• 2016

In this paper, I studied about historical seasonal subdivision system and a theory of traditional monthly order, which was used for so long from Koryo dynasty to the late of Choseon dynasty in Korean histoy. Especially, I took note of the fact that there used the table of solar terms and meteorological observation what we called the table of Kihoo-pyo in the historical Sunmyung-calendar and the Soosi-calendar during the Koryo dynasty. This table of Kihoo was developed for explaining meteorological change during a year at that time. Here are largely four elements related meteorological nature : the first is the list of 24 solar terms, and the second is 12 monthly seasonal terms and 12 monthly central terms, the third is about four right hexagon based I-ching, the fourth is 72 meteorological observations called 72-hoo. Among them, the 72-hoo system is important to know how premodern people observed natural materials including animals and plants, weather, climate about meteorological phenomena according to the seasonal change or solar terms' change during a year. I argued in this article to need developing modern new table of Kihoo system like that, in order to show common people to recognize annual meteorological change more easy and clear. I also argued to need a distinct definition of meteorological seasons from a view point of modern meteorology.