• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.1
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• pp.81-88
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• 2014

Accurate wind data is essential for predicting airborne spread of virus. OpenFOAM was used for computational fluid dynamics (CFD) simulation procedure which is under GNU GPL (General Public License). Using complex terrain, DEM (Digital Elevation Map) that was prepared from GIS information covering a research site is converted to a three dimensional surface mesh that is composed by quad and full hexahedral space meshes. Around this surface mesh, an extended computational domain volume was designed. Atmospheric flow boundary conditions were used at inlet and roughness height and was considered at terrain by using rough wall function. Two different wind conditions that was relatively stable during certain periods were compared in 3 different locations for validating the accuracy of the CFD computed solution. The result shows about 10 % of difference between the calculated result and measured data. This procedure can simulate a prediction of time-series data for airborne virus spread that can be used to make a web-based forecasting system of airborne virus spread.

• Korean Journal of Environmental Biology
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• v.36 no.4
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• pp.507-516
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• 2018

The closed chamber method, which is one of the most commonly used method for measuring greenhouse gases produced in rice paddy fields, has limitations in measuring dynamic $CH_4$ flux with spatio-temporal constrains. In order to deal with the limitation of the closed chamber method, some studies based on open-path of eddy covariance method have been actively conducted recently. The aim of this study was to compare the $CH_4$ fluxes measured by open-path and closed chamber method in the paddy rice fields. The open-path, one of the gas ($CO_2$, $CH_4$ etc.) analysis methods, is technology where a laser beam is emitted from the source passes through the open cell, reflecting multiple times from the two mirrors, and then detecting. The $CH_4$ emission patterns by these two methods during rice cultivation season were similar, but the total $CH_4$ emission measured by open-path method were 31% less than of the amount measured by closed chamber. The reason for the difference in $CH_4$ emission was due to overestimation by closed chamber and underestimation by open-path. The closed chamber method can overestimate $CH_4$ emissions due to environmental changes caused by high temperature and light interruption by acrylic partition in chamber. On the other hand, the open-path method for eddy covariance can underestimate its emission because it assumes density fluctuations and horizontal homogeneous terrain negligible However, comparing $CH_4$ fluxes at the same sampling time (AM 10:30-11:00, 30-min fluxes) showed good agreements ($r^2=0.9064$). The open-path measurement technique is expected to be a good way to compensate for the disadvantage of the closed chamber method because it can monitor dynamic $CH_4$ fluctuation even if data loss is taken into account.

• Journal of Bio-Environment Control
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• v.24 no.3
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• pp.135-146
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• 2015

To provide the data necessary to determine the design wind speed for calculating the wind load acting on a greenhouse, we measured the wind speed below 10m height and analyzed the power law exponents at Buan and Gunwi. A wind speed greater than $5m{\cdot}s^{-1}$ is appropriate for calculating the power law exponent necessary to determine the wind speed distribution function according to height. We observed that the wind speed increased according to a power law function with increased height at Buan, showing a similar trend to the RDC and JGHA standards. Therefore, this result should be applied when determining the power law function for calculating the design wind speed of the greenhouse structure. The ordinary trend is that if terrain roughness increases the value of power law exponent also increases, but in the case of Gunwi the value of power law exponent was 0.06, which shows contrary value than that of the ordinary trend. This contrary trend was due to the elevations difference of 2m between tower installed and surrounding area, which cause contraction in streamline. The power law exponent started to decrease at 7 am, stopped decreasing and started to increase at 3 pm, and stopped increasing and remained constant at 12 pm at Buan. These changes correspond to the general change trends of the power law exponent. The calculated value of the shape parameter for Buan was 1.51, confirming that the wind characteristics at Buan, a reclaimed area near the coast, were similar to those of coastal areas in Jeju.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.346-352
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• 2022

Mountain meteorology in South Korea that is covered mountains with complex terrain is important for understanding and managing the forest disaster and forest ecosystems. In particular, recent changes in dryness and/or rainfall intensity due to climate change may cause an increase in the possibility of forest disasters. Therefore, accurate monitoring of mountain meteorology is needed for efficient forest management. Korea Forest Service (KFS) is establishing the Automatic Mountain Meteorology Observation Stations (AMOS) in the mountain regions since 2012. 464 AMOSs are observing various meteorological variables such as air temperature, relative humidity, wind speed and direction, precipitation, soil temperature, and air pressure for every minute, which is conducted the quality control (QC) to retain data reliability. QC process includes the physical limit test, step test, internal consistency test, persistence test, climate range test, and median filter test. All of AMOS observations are open to use, which can be found from the Korean Mountain Meteorology Information System (KoMIS, http://mtweather.nifos.go.kr/) of the National Institute of Forest Science and the Public Data Portal (https://public.go.kr/). AMOS observations with guaranteed quality can be used in various forest fields including the public safety, forest recreation, forest leisure activities, etc., and can contribute to the advancement of forest science and technology. In this paper, a series of processes are introduced to collect and use the AMOS dataset in the mountain region in South Korea.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.3
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• pp.233-245
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• 2014

Nighttime correction of $CO_2$ flux is one of the most important and challenging tasks in eddy covariance measurements over a complex mountainous terrain. In this study, we have scrutinized the quality and the credibility of the $CO_2$ flux datasets which were produced by employing three different methods of nighttime correction, i.e., (1) friction velocity ($u^*$) correction, (2) light response curve (LRC) correction, and (3) advection-based van Gorsel (VG) correction. The whole year datasets used in our analysis were collected at the two KoFlux tower sites (i.e., GDK deciduous forest site at the upper hill and GCK coniferous forest site at the lower hill) located in the valley of Gwangneung National Arboretum in central Korea. The resultant magnitudes and patterns of ecosystem respiration ($R_E$), gross primary productivity (GPP), and net ecosystem exchange (NEE) of $CO_2$ showed marked differences among the datasets produced with three different correction methods, which were also site-specific. The examination from micrometeorological and ecological perspectives suggests that the major cause of some inconsistency seems to be associated with the advection of $CO_2$ along the sloping terrain and the inappropriate selection of the correction data that might have been already affected by advective flows. The comparison with the results from other studies indicated that the overall characteristics of the corrected $CO_2$ fluxes at GDK and GCK (except those with LRC correction) were well within the ranges reported in the literature for various ecosystems in East Asia in similar latitudes. However, our study also implies that there will be always a room for further improvement in the present datasets. Therefore, caution must be exercised for the data users in order to properly use the updated version of datasets through transparent, open and participatory communication with data producers.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.164-173
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• 2017

Alternative cropping systems would be one of climate change adaptation options. Suitable areas for a crop could be identified using a climate suitability model. The EcoCrop model has been used to assess climate suitability of crops using monthly climate surfaces, e.g., the digital climate map at high spatial resolution. Still, a high-performance computing approach would be needed for assessment of climate suitability to take into account a complex terrain in Korea, which requires considerably large climate data sets. The objectives of this study were to implement a script for R, which is an open source statistics analysis platform, in order to use the EcoCrop model under a parallel computing environment and to assess climate suitability of maize using digital climate maps at high spatial resolution, e.g., 1 km. The total running time reduced as the number of CPU (Central Processing Unit) core increased although the speedup with increasing number of CPU cores was not linear. For example, the wall clock time for assessing climate suitability index at 1 km spatial resolution reduced by 90% with 16 CPU cores. However, it took about 1.5 time to compute climate suitability index compared with a theoretical time for the given number of CPU. Implementation of climate suitability assessment system based on the MPI (Message Passing Interface) would allow support for the digital climate map at ultra-high spatial resolution, e.g., 30m, which would help site-specific design of cropping system for climate change adaptation.