• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1849-1858
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• 2021

We analyzed the monthly and annual trends of the meteorological factors(wind speeds and directions and air temperatures) measured at an automated synoptic observation system (ASOS) and fine particle (PM₁₀ and PM_2.5) concentrations measured at the air quality monitoring systems(AQMSs) in Suwon. In addition, we investigated how the fine particle concentrations were related to the meteorological factors as well as urban morphological parameters (fractions of building volume and road area). We calculated the total volume of buildings and the total area of the roads in the area of 2 km × 2 km centered at each AQMS using the geographic information system and environmental geographic information system. The analysis of the meteorological factors showed that the dominant wind directions at the ASOS were westerly and northwesterly and that the average wind speed was strong in Spring. The measured fine particle concentrations were low in Summer and early Autumn (July to September) and high in Spring and Winter. In 2020, the annual mean fine particle concentration was lowest at most AQMSs. The fine particle concentrations were negatively and weakly correlated with the measured wind speeds and air temperatures (the correlation between PM_2.5 concentrations and air temperatures was relatively strong). In Suwon city, at least for 6 AQMSs except for the RAQMS 131116 and AQMS 131118, the PM₁₀ concentrations were affected mainly by the transport from outside rather than primary emission from mobile sources or wind speed decrease caused by buildings and, in the case of PM_2.5, vise versa.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.83-100
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• 2020

This study evaluated the accuracy of soil moisture and evapotranspiration by calculating the hydrological parameters in Korean peninsula using Land Information System(LIS) developed by US NASA. We used Noah-MP surface model to calculate hydrological parameters, and used MERRA2(Modern-Era Retrospective analysis for Research and Applications, Version 2) for hydrological forcing data. And, International Geosphere-Biosphere Program(IGBP) and University of Maryland(UMD) land cover maps were applied to compare the output accuracy, and Automated Synoptic Observing System(ASOS) of KMA was used as ground observation data. In order to evaluate the accuracy of the output data, the correlation coefficient(CC), BIAS, and efficiency factor (NSE, Nash-Sutcliffe Efficiency) were analyzed with soil moisture and evapotranspiration by ASOS ground observation data. As a result, the correlation coefficient of soil moisture using IGBP was 0.56 on average, and evapotranspiration was about 0.71. On the other hand, soil moisture using UMD was 0.68 on average and evapotranspiration was about 0.72, and the correlation coefficient by UMD was evaluated as high accuracy compared to the results by using IGBP. The correlation coefficient of soil moisture was an average of 0.68 and evapotranspiration was an average of 0.72 when MERRA2 was used as hydrological forcing data. On the other hand, the soil moisture applied with ASOS was an average of 0.66, and evapotranspiration was an average of 0.72. It is judged that the ASOS point data was reanalyzed as 0.65°× 0.5°grids, which is the same spatial resolution with MERRA2, resulting in differences in accuracy depending on the region.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.5-5
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• 2015

현재 우리나라에서 지상관측장비인 AWS(Automatic Weather System)와 ASOS(Automated Synoptic Observing System)기구가 한반도내 668개 지점에서 운영되고 있다. 이러한 장비는 지상관측장비로 하나의 지점에서 측정된 기상변량들이 특정 영역의 대푯값으로 사용되어지고 있다. 기존의 다양한 지점 단위의 수문 모형에서는 지상관측소를 통한 관측값을 적용하기에 어려움 없이 적절한 결과를 도출할 수 있었다. 컴퓨터의 발달로 인하여 복잡한 물리적 현상을 공간적으로 분석할 수 있는 모형의 구동이 가능해짐에 따라서 수문 분야에서도 다양한 분포형 해석 모형이 활발하게 개발 및 적용되고 있다. 지점 관측 자료는 공간적인 연속성을 반영하지 못하는 한계로 인하여 지점 관측자료를 이용한 공간자료의 생성 기법들이 사용되어지고 있지만 자연계에서 나타나는 정확한 공간적 현상을 재현해주지 못하는 문제점이 존재한다. 이러한 지점 관측의 한계를 해결하기 위하여 공간적인 관측이 가능한 레이더와 위성관측과 같은 원격 관측 장비들이 개발되어 공간적으로 연속성을 갖는 기상변량의 취득이 가능하여졌다. TRMM 강우자료는 지구 전체를 0.25도 약 25km 공간해상도를 갖으며 3시간 간격으로 제공되고 있다. 유역단위의 수문모형에 적용하기에 TRMM 강수자료의 공간해상도는 너무 커서 직접적인 적용에 어려움이 있다. 이러한 점에서 TRMM 자료의 상세화 기법을 통하여 수문모형에 적용이 가능한 1km 이하의 고해상도 자료를 생산하는 연구들이 진행되고 있다. 이러한 상세화 방법은 최종적으로 도출하고자 하는 공간해상도를 갖는 대체 변량(지표면 온도, 고도, 식생, 해수면 기압, 상대 습도, 대기온도, 풍향 등)을 이용하여 회귀분석의 형태로 분석이 이루어지고 있다. 그러나 대체 변량을 통해 도출된 상세화된 TRMM 강우는 간접적인 추정으로 인하여 정확한 결과의 도출에는 한계가 있을 것으로 판단된다. 이러한 점에서 본 연구에서는 한반도내 지상 관측값을 공간적 자료로 변환하여 주는데 효과적으로 평가받는 PRISM 모형에 적용하여 기존 SVM 모형을 통한 TRMM 상세화 결과가 갖는 정확성을 평가해 보고 지점 관측자료의 보간 기법의 평가에 TRMM 자료를 활용하는 방안에 대해 평가해 보고자 한다.

• Journal of Korean Society on Water Environment
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• v.34 no.1
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• pp.67-76
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• 2018

There are 34 mega-cities with a population of more than 10 million in the world. One of the highly populated cities in the world is Seoul in South Korea. Seoul receives $1,140million\;m^3/year$ for domestic water, $2million\;m^3/year$ for agricultural water and $6million\;m^3/year$ for industrial water from multi-purpose dams. The maintenance water used for water conservation, ecosystem protection and landscape preservation is $158million\;m^3/year$, which is supplied from natural precipitation. Recently, the use of the other water for preservation of water quality and ecosystem protection in urban areas is increasing. The objectives of this study is to develop the seasonal forecast method of environmental water in urban areas (Seoul, Daejeon, Gwangju, Busan) and to evaluate its predictability. In order to estimate the seasonal outlook information of environmental water from Land Surface Model (LSM), we used the observation weather data of Automated Synoptic Observing System (ASOS) sites, forecast and hind cast data of GloSea5. In the past 30 years (1985 ~ 2014), precipitation, natural runoff and Urban Environmental Water Index (UEI) were analyzed in the 4 urban areas. We calculated the seasonal outlook values of the UEI based on GloSea5 for 2015 year and compared it to UEI based on observed data. The seasonal outlook of UEI in urban areas presented high predictability in the spring, autumn and winter. Studies have depicted that the proposed UEI will be useful for evaluating urban environmental water and the predictability of UEI using GloSea5 forecast data is likely to be high in the order of autumn, winter, spring and summer.

• Journal of Korea Water Resources Association
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• v.56 no.9
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• pp.543-551
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• 2023

Snow is an essential climate factor that affects the climate system and surface energy balance, and it also has a crucial role in water balance by providing solid water stored during the winter for spring runoff and groundwater recharge. In this study, statistical analysis of Local Data Assimilation and Prediction System (LDAPS), Modern.-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), and ERA5-Land snow depth data were used to evaluate the applicability in South Korea. The statistical analysis between the Automated Synoptic Observing System (ASOS) ground observation data provided by the Korea Meteorological Administration (KMA) and the reanalysis data showed that LDAPS and ERA5-Land were highly correlated with a correlation coefficient of more than 0.69, but LDAPS showed a large error with an RMSE of 0.79 m. In the case of MERRA-2, the correlation coefficient was lower at 0.17 because the constant value was estimated continuously for some periods, which did not adequately simulate the increase and decrease trend between data. The statistical analysis of LDAPS and ASOS showed high and low performance in the nearby Gangwon Province, where the average snowfall is relatively high, and in the southern region, where the average snowfall is low, respectively. Finally, the error variance between the four independent snow depth data used in this study was calculated through triple collocation (TC), and a merged snow depth data was produced through weighting factors. The reanalyzed data showed the highest error variance in the order of LDAPS, MERRA-2, and ERA5-Land, and LDAPS was given a lower weighting factor due to its higher error variance. In addition, the spatial distribution of ERA5-Land snow depth data showed less variability, so the TC-merged snow depth data showed a similar spatial distribution to MERRA-2, which has a low spatial resolution. Considering the correlation, error, and uncertainty of the data, the ERA5-Land data is suitable for snow-related analysis in South Korea. In addition, it is expected that LDAPS data, which is highly correlated with other data but tends to be overestimated, can be actively utilized for high-resolution representation of regional and climatic diversity if appropriate corrections are performed.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1837-1847
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• 2021

This study investigated wind corridors for the entire Suwon-city area using a geographic information system and a computational fluid dynamics model. We conducted numerical simulations for 16 inflow wind directions using the average wind speeds measured at the Suwon automated synoptic observation system (ASOS) for recent ten years. We analyzed the westerly (dominant wind direction) and easterly cases (not dominant but strong wind speed) in detail and investigated the characteristics of a wind speed distribution averaged using the frequencies of 16 wind directions as weighting factors. The characteristics of the wind corridors in Suwon city can be summarized as; (1) In the northern part of Suwon, complicated flows were formed by the high mountainous terrain, and strong (weak) winds and updrafts (downdrafts) were simulated on the windward (leeward) mountain slope. (2) On the leeward mountain slope, a wind corridor was formed along a valley, and relatively strong airflow flowed into the residential area. (3) The strong winds were simulated in a wide and flat area in the west and south part of Suwon city. (4) Due to the friction and flow blocking by buildings, wind speeds decreased, and airflows became complicated in the downtown area. (5) Wind corridors in residential areas were formed along wide roads and areas with few obstacles, such as rivers, lakes, and reservoirs.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.603-616
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• 2016

In this study, the effects of differential heating by land-use types on flow and air temperature at an Seoul Automated Synoptic Observing Systems (ASOS) located at Songwol-dong, Jongno-gu, Seoul was analyzed. For this, a computation fluid dynamics (CFD) model was coupled to the local data assimilation and prediction system (LDAPS) for reflecting the local meteorological characteristics at the boundaries of the CFD model domain. Time variation of temperatures on solid surfaces was calculated using observation data at El-Oued, Algeria of which latitude is similar to that of the target area. Considering land-use type and shadow, surface temperatures were prescribed in the LDAPS-CFD coupled model. The LDAPS overestimated wind speeds and underestimated air temperature compared to the observations. However, a coupled LDAPS-CFD model relatively well reproduced the observed wind speeds and air temperature, considering complicated flows and surface temperatures in the urban area. In the morning when the easterly was dominant around the target area, both the LDAPS and coupled LDAPS-CFD model underestimated the observed temperatures at the Seoul ASOS. This is because the Kyunghee Palace located at the upwind region was composed of green area and its surface temperature was relatively low. However, in the afternoon when the southeasterly was dominant, the LDAPS still underestimated, on the while, the coupled LDAPS-CFD model well reproduced the observed temperatures at the Seoul ASOS by considering the building-surface heating.

• Journal of the Korean association of regional geographers
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• v.19 no.3
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• pp.384-400
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• 2013

In this study, spatio-temporal patterns of extreme precipitation events caused by typhoons are examined based on observational daily precipitation data at approximately 340 weather stations of Korea Meterological Administration's ASOS (Automated Synoptic Observation System) and AWS (Automatic Weather System) networks for the recent 10 year period (2002~2011). Generally, extreme precipitation events by typhoons exceeding 80mm of daily precipitation commonly appear in Jeju Island, Gyeongsangnam-do, and the eastern coastal regions of the Korean Peninsula. However, the frequency, intensity and spatial extent of typhoon-driven extreme precipitation events can be modified depending on the topography of major mountain ridges as well as the pathway of and proximity to typhoons accompanying the anti-clockwise circulation of low-level moisture with hundreds of kilometers of radius. Yellow Sea-passing type of typhoons in July cause more frequent extreme precipitation events in the northern region of Gyeonggi-do, while East Sea-passing type or southern-region-landfall type of typhoons in August-early September do in the interior regions of Gyeongsangnam-do. These results suggest that when local governments develop optimal mitigation strategies against potential damages by typhoons, the pathway of and proximity to typhoons are key factors.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.2
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• pp.122-133
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• 2021

Cultivar parameter calibration can be affected by the reliability of the input data to a crop growth model. In South Korea, two sets of weather stations, which are included in the automated synoptic observing system (ASOS) or the automatic weather system (AWS), are available for preparation of the weather input data. The objectives of this study were to estimate the cultivar parameter using those sets of weather data and to compare the uncertainty of these parameters. The cultivar parameters of CERES-Rice model for Shindongjin cultivar was calibrated using the weather data measured at the weather stations included in either ASO S or AWS. The observation data of crop growth and management at the experiment farms were retrieved from the report of new cultivar development and research published by Rural Development Administration. The weather stations were chosen to be the nearest neighbor to the experiment farms where crop data were collected. The Generalized Likelihood Uncertainty Estimation (GLUE) method was used to calibrate the cultivar parameters for 100 times, which resulted in the distribution of parameter values. O n average, the errors of the heading date decreased by one day when the weather input data were obtained from the weather stations included in AWS compared with ASO S. In particular, reduction of the estimation error was observed even when the distance between the experiment farm and the ASOS stations was about 15 km. These results suggest that the use of the AWS stations would improve the reliability and applicability of the crop growth models for decision support as well as parameter calibration.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.155-163
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• 2022

The optimization of long-range ensemble climate prediction for rice phenology model with advanced bias correction method is conducted. The daily long-range forecast(6-month) of mean/ minimum/maximum temperature and observation of January to October during 1991-2021 is collected for rice phenology prediction. In this study, the concept of "buffer period" is newly introduced to reduce the problem after bias correction by quantile mapping with constructing the transfer function by month, which evokes the discontinuity at the borders of each month. The four experiments with different lengths of buffer periods(5, 10, 15, 20 days) are implemented, and the best combinations of buffer periods are selected per month and variable. As a result, it is found that root mean square error(RMSE) of temperatures decreases in the range of 4.51 to 15.37%. Furthermore, this improvement of climatic variables quality is linked to the performance of the rice phenology model, thereby reducing RMSE in every rice phenology step at more than 75~100% of Automated Synoptic Observing System stations. Our results indicate the possibility and added values of interdisciplinary study between atmospheric and agriculture sciences.