• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.1
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• pp.13-34
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• 2022

Soil moisture data have been collected at 11 agrometeorological stations operated by The Korea Meteorological Administration (KMA). This study aimed to verify the accuracy of soil moisture data of KMA and develop a correction formula to be applied to improve their quality. The soil of the observation field was sampled to analyze its physical properties that affect soil water content. Soil texture was classified to be sandy loam and loamy sand at most sites. The bulk density of the soil samples was about 1.5 g/cm³ on average. The content of silt and clay was also closely related to bulk density and water holding capacity. The EnviroSCAN model, which was used as a reference sensor, was calibrated using the self-manufactured "reference soil moisture observation system". Comparison between the calibrated reference sensor and the field sensor of KMA was conducted at least three times at each of the 11 sites. Overall, the trend of fluctuations over time in the measured values of the two sensors appeared similar. Still, there were sites where the latter had relatively lower soil moisture values than the former. A linear correction formula was derived for each site and depth using the range and average of the observed data for the given period. This correction formula resulted in an improvement in agreement between sensor values at the Suwon site. In addition, the detailed approach was developed to estimate the correction value for the period in which a correction formula was not calculated. In summary, the correction of soil moisture data at a regular time interval, e.g., twice a year, would be recommended for all observation sites to improve the quality of soil moisture observation data.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2001.06a
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• pp.43-48
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• 2001

Many applications in the areas of agricultural, hydrological and environmental resource management require data over very large areas and with a high imaging frequency - monitoring crop growth, water stress, seasonal wetland flooding and natural vegetation development. This precludes the use of fine resolution data (Landsat, Spot) on the grounds of cost, accessibility and low imaging frequency. Meteorological satellites have the potential to fill this need, given their very wide spatial coverage, and high repeat imaging. The Remote Sensing Unit (RSU) at the Zambia Meteorological Department routinely receives, processes and archives imagery from both Meteosat and NOAA AVHRR satellites. Here I wish to present some examples of applications of these data sets that arise from the RSU work - relationships between rainfall and vegetation development as assessed by satellite, derived information and seasonal patterns of flooding in the Barotse floodplain and the Kafue flats. I also wish to outline ways in which a more widespread use of this data by the Zambian institutions canbe achieved.

• Atmosphere
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• v.29 no.4
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• pp.501-509
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• 2019

Asian Dust is a meteorological phenomenon that sand particles are raised from the arid and semi-arid regions-Taklamakan Desert, Gobi Desert and Inner Mongolia in China-and transported by westerlies and deposited on the surface. Asian dust results in a negative effect on human health as well as environmental, social and economic aspects. For monitoring of Asian Dust, Korea Meteorological Administration operates 29 stations using a continuous ambient particulate monitor. Kim et al. (2016) developed an automatic quality check (AQC) algorithm for objective and systematic quality check of observed PM₁₀ concentration and evaluated AQC with results of a manual quality check (MQC). The results showed the AQC algorithm could detect abnormal observations efficiently but it also presented a large number of false alarms which result from valid error check. To complement the deficiency of AQC and to develop an AQC system which can be applied in real-time, AQC has been modulated. Based on the analysis of instrument status codes, valid error check process was revised and 6 status codes were further considered as normal. Also, time continuity check and spike check were modified so that posterior data was not referred at inspection time. Two-year observed PM₁₀ concentration data and corresponding MQC results were used to evaluate the modulated AQC compared to the original AQC algorithm. The results showed a false alarm ratio decreased from 0.44 to 0.09 and the accuracy and the probability of detection were conserved well in spite of the exclusion of posterior data at inspection time.

• Proceedings of the KSRS Conference
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• v.1
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• pp.278-281
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• 2006

Korea Meteorological Administration(KMA) has issued the tropical storm(typhoon) warning or advisories when it was developed to tropical storm from tropical depression and a typhoon is expected to influence the Korean peninsula and adjacent seas. Typhoon information includes current typhoon position and intensity. KMA has used the Dvorak Technique to analyze the center of typhoon and it's intensity by using available geostationary satellites' images such as GMS, GOES-9 and MTSAT-1R since 2001. The Dvorak technique is so subjective that the analysis results could be variable according to analysts. To reduce the subjective errors, QuikSCAT seawind data have been used with various analysis data including sea surface temperature from geostationary meteorological satellites, polar orbit satellites, and other observation data. On the other hand, there is an advantage of using the Subjective Dvorak Technique(SDT). SDT can get information about intensity and center of typhoon by using only infrared images of geostationary meteorology satellites. However, there has been a limitation to use the SDT on operational purpose because of lack of observation and information from polar orbit satellites such as SSM/I. Therefore, KMA has established Advanced Objective Dvorak Technique(AODT) system developed by UW/CIMSS(University of Wisconsin-Madison/Cooperative Institude for Meteorological Satellite Studies) to improve current typhoon analysis technique, and the performance has been tested since 2005. We have developed statistical relationships to correct AODT CI numbers according to the SDT CI numbers that have been presumed as truths of typhoons occurred in northwestern pacific ocean by using linear, nonlinear regressions, and neural network principal component analysis. In conclusion, the neural network nonlinear principal component analysis has fitted best to the SDT, and shown Root Mean Square Error(RMSE) 0.42 and coefficient of determination($R^2$) 0.91 by using MTSAT-1R satellite images of 2005. KMA has operated typhoon intensity analysis using SDT and AODT since 2006 and keep trying to correct CI numbers.

• Atmosphere
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• v.25 no.3
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• pp.483-499
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• 2015

This study examined the impact of change of land-use and meteorological condition due to urbanization on heat environment in Seoul metropolitan area over a decade (2000 and 2009) using Weather Research and Forecasting (WRF)-Urban Canopy Model (UCM). The numerical simulations consist of three sets: meteorological conditions of (1) October 2000 with land-use data in 2000 (base simulation), (2) October 2009 with land-use data in 2000 (meteorological condition change effect) and (3) October 2009 with land-use data in 2009 (both the effects of land-use and meteorological condition change). According to the experiment results, the change of land-use and meteorological condition by urbanization over a decade showed different contribution to the change of heat environment in Seoul metropolitan area. There was about $1^{\circ}C$ increase in near-surface (2 m) temperature over all of the analyzed stations due to meteorological condition change. In stations where the land-use type changed into urban, large temperature increase at nighttime was observed by combined effects of meteorological condition and land-use changes (maximum $4.23^{\circ}C$). Urban heat island (UHI) over $3^{\circ}C$ (temperature difference between Seoul and Okcheon) increased 5.24% due to the meteorological condition change and 26.61% due to the land-use change. That is, land-use change turned out to be contributing to the strengthening of UHI more than the meteorological condition change. Moreover, the land-use change plays a major role in the increase of sensible heat flux and decrease of latent heat flux.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.1
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• pp.11-18
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• 2012

Daily temperature data produced by harmonic analysis of monthly climate summary have been used as an input to plant phenology model. This study was carried out to evaluate the performance of the harmonic based daily temperature data in prediction of major phenological developments and to apply the results in improving decision support for agricultural production in relation to the climate change scenarios. Daily maximum and minimum temperature data for a climatological normal year (Jan. 1 to Dec. 31, 1971-2000) were produced by harmonic analysis of the monthly climate means for Seoul weather station. The data were used as inputs to a thermal time - based phenology model to predict dormancy, budburst, and flowering of Japanese cherry in Seoul. Daily temperature measurements at Seoul station from 1971 to 2000 were used to run the same model and the results were compared with the harmonic data case. Leaving no information on annual variation aside, the harmonic based simulation showed 25 days earlier release from endodormancy, 57 days longer period for maximum cold tolerance, delayed budburst and flowering by 14 and 13 days, respectively, compared with the simulation based on the observed data. As an alternative to the harmonic data, 30 years daily temperature data were generated by a stochastic process (SIMMETEO + WGEN) using climatic summary of Seoul station for 1971-2000. When these data were used to simulate major phenology of Japanese cherry for 30 years, deviations from the results using observed data were much less than the harmonic data case: 6 days earlier dormancy release, 10 days reduction in maximum cold tolerance period, only 3 and 2 days delay in budburst and flowering, respectively. Inter-annual variation in phenological developments was also in accordance with the observed data. If stochastically generated temperature data could be used in agroclimatic mapping and zoning, more reliable and practical aids will be available to climate change adaptation policy or decision makers.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.283-294
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• 2021

Solar radiation is an important meteorological factor in the agricultural sector. The ground exposed to sunlight is highly influenced by the surrounding terrains especially in South Korea where the topology is complex. The solar radiation on an inclined surface is estimated using a solar irradiance correction factor for the slope of the terrain along with the solar radiation on a horizontal surface. However, such an estimation method assumes that there is no barrier in surroundings, which blocks sunlight from the sky. This would result in errors in estimation of solar radiation because the effect of shading caused by the surrounding terrain has not been taken into account sufficiently. In this study, the shading effect was simulated to obtain the brightness value (BV), which was used as a correction factor. The shaded relief images, which were generated using a 30m-resolution digital elevation model (DEM), were used to derive the BVs. These images were also prepared using the position of the sun and the relief of the terrain as inputs. The gridded data where the variation of direct solar radiation was quantified as brightness were obtained. The value of cells in the gridded data ranged from 0 (the darkest value) to 255 (the brightest value). The BV analysis was performed using meteorological observation data at 22 stations installed in study area. The observed insolation was compared with the BV of each point under clear and cloudless condition. It was found that brightness values were significantly correlated with the solar radiation, which confirmed that shading due to terrain could explain the variation in direct solar radiation. Further studies are needed to accurately estimate detailed solar radiation using shaded relief images and brightness values.

• Atmosphere
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• v.25 no.2
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• pp.221-233
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• 2015

Pollen is closely related to health issues such as allergenic rhinitis and asthma as well as intensifying atopic syndrome. Information on current and future spatio-temporal distribution of allergenic pollen is needed to address such issues. In this study, the Community Multiscale Air Quality Modeling (CMAQ) was utilized as a base modeling system to forecast pollen dispersal from oak trees. Pollen emission is one of the most important parts in the dispersal modeling system. Areal emission factor was determined from gridded areal fraction of oak trees, which was produced by the analysis of the tree type maps (1:5000) obtained from the Korea Forest Service. Daily total pollen production was estimated by a robust multiple regression model of weather conditions and pollen concentration. Hourly emission factor was determined from wind speed and friction velocity. Hourly pollen emission was then calculated by multiplying areal emission factor, daily total pollen production, and hourly emission factor. Forecast data from the KMA UM LDAPS (Korea Meteorological Administration Unified Model Local Data Assimilation and Prediction System) was utilized as input. For the verification of the model, daily observed pollen concentration from 12 sites in Korea during the pollen season of 2014. Although the model showed a tendency of over-estimation in terms of the seasonal and daily mean concentrations, overall concentration was similar to the observation. Comparison at the hourly output showed distinctive delay of the peak hours by the model at the 'Pocheon' site. It was speculated that the constant release of hourly number of pollen in the modeling framework caused the delay.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.446-454
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• 2023

The impact of climate change on agriculture is substantial, especially as global warming is projected to lead to varying temperature and humidity patterns in the future. These changes pose a higher risk for both crops and livestock, exposing them to environmental stressors under altered climatic conditions. Specifically, as temperatures are expected to rise, the risk of heat stress is assessable through the Temperature-Humidity Index (THI), derived from temperature and relative humidity data. This study involved the comparison of THI collected from 10 Korea Meteorological Administration ASOS stations spanning a 60-year period from 1961 to 2020. Moreover, high-resolution temperature and humidity distribution data from 1981 to 2020 were employed to generate high-resolution TH I distributions, analyzing temporal changes. Additionally, the number of days characterized by heat stress, derived from TH I, was compared over different time periods. Generally, TH I showed an upward trend over the past, albeit with varying rates across different locations. As TH I increased, the frequency of heat stress days also rose, indicating potential future cost increases in the livestock industry due to heat-related challenges. The findings emphasize the feasibility of evaluating heat stress risk in livestock using THI and underscore the need for research analyzing THI under future climate change scenarios.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.1
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• pp.5-17
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• 2018

The standardized eddy covariance flux data processing in KoFlux has been updated, and its database has been amended accordingly. KoFlux data users have not been informed properly regarding these changes and the likely impacts on their analyses. In this paper, we have documented how the current structure of data processing in KoFlux has been established through the changes and improvements to ensure transparency, reliability and usability of the KoFlux database. Due to increasing diversity and complexity of flux site instrumentation and organization, we have re-implemented the previously ignored or simplified procedures in data processing (e.g., frequency response correction, stationarity test), and added new methods for $CH_4$ flux gap-filling and $CO_2$ flux correction and partitioning. To evaluate the effects of the changes, we processed the data measured at a flat and homogeneous paddy field (i.e., HPK) and a deciduous forest in complex and heterogeneous topography (i.e., GDK), and quantified the differences. Based on the results from our overall assessment, it is confirmed that (1) the frequency response correction (HPK: 11~18% of biases for annually integrated values, GDK: 6~10%) and the stationarity test (HPK: 4~19% of biases for annually integrated values, GDK: 9~23%) are important for quality control and (2) the minimization of the missing data and the choice of the appropriate driver (rather than the choice of the gap-filling method) are important to reduce the uncertainty in gap-filled fluxes. These results suggest the future directions for the data processing technology development to ensure the continuity of the long-term KoFlux database.