Kyu Rang Kim;Eunsu Jo;Myeong Su Ko;Jung Hyuk Kang;Yunjae Hwang;Yong Hee Lee
Korean Journal of Agricultural and Forest Meteorology
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v.26
no.1
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pp.63-74
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2024
In agriculture, frost can be devastating, which is why observation and forecasting are so important. According to a recent report analyzing frost observation data from the Korea Meteorological Administration, despite global warming due to climate change, the late frost date in spring has not been accelerated, and the frequency of frost has not decreased. Therefore, it is important to automate and continuously operate frost observation in risk areas to prevent agricultural frost damage. In the existing frost observation using leaf wetness sensors, there is a problem that the reference voltage value fluctuates over a long period of time due to contamination of the observation sensor or changes in the humidity of the surrounding environment. In this study, a datalogger program was implemented to automatically solve these problems. The established frost observation system can stably and automatically accumulate time-resolved observation data over a long period of time. This data can be utilized in the future for the development of frost diagnosis models using machine learning methods and the production of frost occurrence prediction information for surrounding areas.
Korean Journal of Agricultural and Forest Meteorology
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v.25
no.3
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pp.226-235
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2023
This study aimed to supplement the shortcomings of the Multiple-sensor-based Frost Observation System (MFOS). The developed frost observation system is an improvement of the existing system. Based on the leaf wetness sensor (LWS), it not only detects frost but also functions to predict surface temperature, which is a major factor in frost occurrence. With the existing observation system, 1) it is difficult to observe ice (frost) formation on the surface when capturing an image of the LWS with an RGB camera because the surface of the sensor reflects most visible light, 2) images captured using the RGB camera before and after sunrise are dark, and 3) the thermal infrared camera only shows the relative high and low temperature. To identify the ice (frost) generated on the surface of the LWS, a LWS that was painted black and three sheets of glass at the same height to be used as an auxiliary tool to check the occurrence of ice (frost) were installed. For RGB camera shooting before and after sunrise, synchronous LED lighting was installed so the power turns on/off according to the camera shooting time. The existing thermal infrared camera, which could only assess the relative temperature (high or low), was improved to extract the temperature value per pixel, and a comparison with the surface temperature sensor installed by the National Institute of Meteorological Sciences (NIMS) was performed to verify its accuracy. As a result of installing and operating the MFOS v2, which reflects these improvements, the accuracy and efficiency of automatic frost observation were demonstrated to be improved, and the usefulness of the data as input data for the frost prediction model was enhanced.
Kim, Suhyun;Lee, Seung-Jae;Son, Seungwon;Cho, Sungsik;Jo, Eunsu;Kim, Kyurang
Korean Journal of Agricultural and Forest Meteorology
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v.24
no.2
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pp.95-114
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2022
This study presented the possibility of automatic frost observation and the related image data acquisition through the design and installation of a Multiple-sensor based Frost Observation System (MFOS). The MFOS is composed of an RGB camera, a thermal camera and a leaf wetness sensor, and each device performs complementary roles. Through the test operation of the equipment before the occurrence of frost, the voltage value of the leaf wetness sensor increased when maintaining high relative humidity in the case of no precipitation. In the case of Gapyeong- gun, the high relative humidity was maintained due to the surrounding agricultural waterways, so the voltage value increased significantly. In the RGB camera image, leaf wetness sensor and the surface were not observed before sunrise and after sunset, but were observed for the rest of the time. In the case of precipitation, the voltage value of the leaf wetness sensor rapidly increased during the precipitation period and decreased after the precipitation was terminated. In the RGB camera image, the leaf wetness sensor and surface were observed regardless of the precipitation phenomenon, but the thermal camera image was taken due to the precipitation phenomenon, but the leaf wetness sensor and surface were not observed. Through, where actual frost occurred, it was confirmed that the voltage value of leaf wetness sensor was higher than the range corresponding to frost, but frost was observed on the surface and equipment surface by the RGB camera.
Jo, Eunsu;Kim, Hae-Min;Shin, Ju-Young;Kim, Kyu Rang;Lee, Yong Hee;Jee, Joonbum
Korean Journal of Agricultural and Forest Meteorology
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v.24
no.2
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pp.83-94
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2022
In order to actively prepare to frost damage that occurs in the process of growing crops, the spatial and temporal distribution of frost occurrence in South Korea was derived using frost observation data from 20 regions over the past 21 years (2000~2020). The main products are the number of frost days, first frost day, and last frost day by region. And the climatic trends of these results were identified by performing the Mann-Kendall trend test and Sen's slope estimator. In South Korea, a lot of frost occurs in the inland area to the west of the Taebaek and Sobaek Mountains. Relatively closer to the coastal area, the number of frost days is small, the first frost day is slow, and the last frost day is early. The east coast region has fewer frost days, the first frost day is later, and the last frost day is earlier than the west coast region. The southern sea, the southeastern sea region, and the island region rarely experience frost. As a result of the annual time series trend analysis, although South Korea is a country where climate warming is progressing, there was no trend in reducing the number of frost days and slowing the first frost day, and it was found that the last frost day is delayed by 0.5 days per year.
When frost occurs, crops are directly damaged. When crops come into contact with low temperatures, tissues freeze, which hardens and destroys the cell membranes or chloroplasts, or dry cells to death. In July 2020, a sudden sub-zero weather and frost hit the Minas Gerais state of Brazil, the world's largest coffee producer, damaging about 30% of local coffee trees. As a result, coffee prices have risen significantly due to the damage, and farmers with severe damage can produce coffee only after three years for crops to recover, which is expected to cause long-term damage. In this paper, we tried to predict frost using frost generation data and weather observation data provided by the Korea Meteorological Administration to prevent severe frost. A model was constructed by reflecting weather factors such as wind speed, temperature, humidity, precipitation, and cloudiness. Using XGB(eXtreme Gradient Boosting), SVM(Support Vector Machine), Random Forest, and MLP(Multi Layer perceptron) models, various hyper parameters were applied as training data to select the best model for each model. Finally, the results were evaluated as accuracy(acc) and CSI(Critical Success Index) in test data. XGB was the best model compared to other models with 90.4% ac and 64.4% CSI, followed by SVM with 89.7% ac and 61.2% CSI. Random Forest and MLP showed similar performance with about 89% ac and about 60% CSI.
Korean Journal of Agricultural and Forest Meteorology
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v.4
no.3
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pp.133-140
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2002
Site-specific minimum temperature forecasts are critical in a short-term decision making procedure for preventive measures as well as a long-term strategy such as site selection in fruits industry. Nocturnal cold air pools frequently termed in mountainous areas under anticyclonic systems are very dangerous to the flowering buds in spring over Korea, but the spatial resolution to detect them exceeds the current weather forecast scale. To supplement the insufficient spatial resolution of official forecasts, we developed a GIS - assisted frost risk assesment scheme for using in mountainous areas. Daily minimum temperature data were obtained from 6 sites located in a 2.1 by 2.1 km area with complex topography near the southern edge of Sobaek mountains during radiative cooling nights in spring 2001. A digital elevation model with a 10 m spatial resolution was prepared for the entire study area and the cold air inflow was simulated for each grid cell by counting the number of surrounding cells coming into the processing cell. Primitive temperature surfaces were prepared for the corresponding dates by interpolating the Korea Meteorological Administration's automated observational data with the lapse rate correction. The cell temperature values corresponding to the 6 observation sites were extracted from the primitive temperature surface, and subtracted from the observed values to obtain the estimation error. The errors were regressed to the flow accumulation at the corresponding cells, delineating a statistically significant relationship. When we applied this relationship to the primitive temperature surfaces of frost nights during April 2002, there was a good agreement with the observations, showing a feasibility of site-specific frost warning system development in mountainous areas.
During the whole month of December in 2005, Korea experienced both heavy snowfall and freezing temperature in southeast regions, which had caused frost related damages to many pavements laid on top of box culverts. In-situ observation revealed that the formation of ice lenses in subgrade and subsequent unbound layers led to upward heaving and transverse cracks in concrete and asphalt pavements. This has affected the long-term performance of pavements, as well as has threatened drivers' safety for a while. Recently, Korea Expressway Corporation has proposed a design guide to better protect newly constructed unbound pavement layers over culverts from frost heave. A trench drainage system has been selected to effectively draw off water and to alleviate pore-water pressure in soils during the coldest season. This paper presents experimental and analytical backgrounds behind this new design guide. Soil specimens retrieved from the sites are tested to quantify clay content and to estimate the permeability of subgrade. A 2-D ground seepage analysis has been conducted to better understand the changes in pore water pressures as a function of grain size. Finally, an optimum size of trench drainage is determined based on numerical analysis and workability in the field.
Journal of The Geomorphological Association of Korea
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v.25
no.1
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pp.47-65
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2018
Frost shattering has traditionally been considered as one of the most effective process in rock weathering. Each slab specimens of five or six rhyolite, basalt and tuff was prepared and put in freeze-thaw cycles and repeated 300 times in the temperature of $-25^{\circ}C$ to $+30^{\circ}C$ and their weathering patterns and products were analyzed by surface observation, particle size, XRD and thin section. As the result, some changes were observed in weathering patterns and weathering products. Rock shattering was more active in waterlogging rather than atmospheric conditions, but there are many differences depending on the type of rock. Rhyolite is hardly weathered by 300 times freeze-thaw cycles and generates the least amount of weathering products. Weathering of Basalt is limited to the surface layer where water can be absorbed, and produces a few amount of platy-shape debris. Tuff are separated by blocky structure which the particles are aggregated along their edges rather than enlarged existing cracks/joins or generated new joints.
Korean Journal of Agricultural and Forest Meteorology
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v.6
no.1
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pp.49-60
/
2004
Northern Gyeonggi Province(NGP), consisting of 3 counties, is the northernmost region in South Korea adjacent to the de-militarized zone with North Korea. To supplement insufficient spatial coverage of official climate data and climate atlases based on those data, high-resolution digital climate models(DCM) were prepared to support weather- related activities of residents in NGP Monthly climate data from 51 synoptic stations across both North and South Korea were collected for 1981-2000. A digital elevation model(DEM) for this region with 30m cell spacing was used with the climate data for spatially interpolating daily maximum and minimum temperatures, solar irradiance, and precipitation based on relevant topoclimatological models. For daily minimum temperature, a spatial interpolation scheme accommodating the potential influences of cold air accumulation and the temperature inversion was used. For daily maximum temperature estimation, a spatial interpolation model loaded with the overheating index was used. Daily solar irradiances over sloping surfaces were estimated from nearby synoptic station data weighted by potential relative radiation, which is the hourly sum of relative solar intensity. Precipitation was assumed to increase with the difference between virtual terrain elevation and the DEM multiplied by an observed rate. Validations were carried out by installing an observation network specifically for making comparisons with the spatially estimated temperature pattern. Freezing risk in January was estimated for major fruit tree species based on the DCMs under the recurrence intervals of 10, 30, and 100 years, respectively. Frost risks at bud-burst and blossom of tree flowers were also estimated for the same resolution as the DCMs.
Korean Journal of Agricultural and Forest Meteorology
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v.17
no.4
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pp.384-398
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2015
In this paper, the high-resolution Weather Research and Forecasting/Noah-MultiParameterization (WRF/Noah-MP) modeling system is configured for the Cheongmicheon Farmland site in Korea (CFK), and its performance in land and atmospheric simulation is evaluated using the observed data at CFK during the 2014 special observation period (21 August-10 September). In order to explore the usefulness of turning on Noah-MP dynamic vegetation in midterm simulations of surface and atmospheric variables, two numerical experiments are conducted without dynamic vegetation and with dynamic vegetation (referred to as CTL and DVG experiments, respectively). The main results are as following. 1) CTL showed a tendency of overestimating daytime net shortwave radiation, thereby surface heat fluxes and Bowen ratio. The CTL experiment showed reasonable magnitudes and timing of air temperature at 2 m and 10 m; especially the small error in simulating minimum air temperature showed high potential for predicting frost and leaf wetness duration. The CTL experiment overestimated 10-m wind and precipitation, but the beginning and ending time of precipitation were well captured. 2) When the dynamic vegetation was turned on, the WRF/Noah-MP system showed more realistic values of leaf area index (LAI), net shortwave radiation, surface heat fluxes, Bowen ratio, air temperature, wind and precipitation. The DVG experiment, where LAI is a prognostic variable, produced larger LAI than CTL, and the larger LAI showed better agreement with the observed. The simulated Bowen ratio got closer to the observed ratio, indicating reasonable surface energy partition. The DVG experiment showed patterns similar to CTL, with differences for maximum air temperature. Both experiments showed faster rising of 10-m air temperature during the morning growth hours, presumably due to the rapid growth of daytime mixed layers in the Yonsei University (YSU) boundary layer scheme. The DVG experiment decreased errors in simulating 10-m wind and precipitation. 3) As horizontal resolution increases, the models did not show practical improvement in simulation performance for surface fluxes, air temperature, wind and precipitation, and required three-dimensional observation for more agricultural land spots as well as consistency in model topography and land cover data.
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