• Journal of Korea Water Resources Association
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• v.52 no.5
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• pp.337-347
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• 2019

This study proposes the framework to select the representative general circulation model (GCM) for climate change projection. The grid-based results of GCMs were transformed to all considered meteorological stations using inverse distance weighted (IDW) method and its results were compared to the observed precipitation. Six quantile mapping methods and random forest method were used to correct the bias between GCM's and the observation data. Thus, the empirical quantile which belongs to non-parameteric transformation method was selected as a best bias correction method by comparing the measures of performance indicators. Then, one of the multi-criteria decision techniques, TOPSIS (Technique for Order of Preference by Ideal Solution), was used to find the representative GCM using the performances of four GCMs after the bias correction using empirical quantile method. As a result, GISS-E2-R was the best and followed by MIROC5, CSIRO-Mk3-6-0, and CCSM4. Because these results are limited several GCMs, different results will be expected if more GCM data considered.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.2
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• pp.144-155
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• 2015

Since the relocation project of equipment in 2011, the overall circumstances of KMA's agrometeorological observation have been significantly improved. Some concerns, however, emerged as a result of the evaluation of observational circumstances in terms of quality assurance after the field surveys on all stations. In order to improve the situation, we suggest: (1) establishment of clear management responsibilities, (2) enhancement of mutual cooperation system between relevant organizations, (3) detailed records of the changes in the observational circumstances, (4) standardization of equipment and sensors, (5) installation of unified information boards, (6) transfer of inappropriate facilities to an adjacent cropland and (7) setup of automated evaporation pan. In order to effectively utilize the high-quality data obtained through improvement of observational circumstances and an elaborate quality control, it is recommended to publish and disseminate regular reports on agrometeorological observations. To produce such a report on a trial basis, we have investigated different types of regular reports issued by domestic and foreign organizations, publication periods, geographical scope, main contents and amount. Based on our current situation, it would be beneficial to learn from the cases of Germany and Canada, which summarize mainly the distinctive agrometeorological phenomena occurred over the past years across the country.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.4
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• pp.298-303
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• 2013

In this study, the installation effects of a windbreak net on reducing wind speed were examined using meteorological observation data. Three automatic weather systems (AWS) were installed at the inside of the windbreak net of an apple orchard along the distance, and one AWS was located at the outside. They were set up on Oct. $25^{th}$, 2012 at the apple orchard of Geochang County, and meteorological data, which were observed at four stations for about 1 year from October 26, 2012 through October 21, 2013, were used for this study. Meteorological variables include air temperature & relative humidity at a height of 1.5 meter, and wind speed & wind direction at a height of 2 meter and 4 meter. These variables were measured and recorded every 60 seconds. The preliminary results of this study was as follows: (1) Daily mean temperature at the inside of the windbreak net was lower than that of the outside by 0.1 through $0.2^{\circ}C$. (2) Daily mean relative humidity at the inside of the windbreak net was higher than that of the outside by 0.7 through 1.7%. (3) As compared to the outside, northerly daily maximum wind speed of the inside of the windbreak net at a height of 2 and 4 meter was reduced by 0.7~1.5 $ms^{-1}$ (30.4~65.2%) and 0.3~0.7 $ms^{-1}$ (10.3~24.1%), respectively.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.2
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• pp.85-96
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• 2019

Solar radiation is an important variable for estimation of energy balance and water cycle in natural and agricultural ecosystems. A deep neural network (DNN) model has been developed in order to estimate the daily global solar radiation. Temperature and precipitation, which would have wider availability from weather stations than other variables such as sunshine duration, were used as inputs to the DNN model. Five-fold cross-validation was applied to train and test the DNN models. Meteorological data at 15 weather stations were collected for a long term period, e.g., > 30 years in Korea. The DNN model obtained from the cross-validation had relatively small value of RMSE ($3.75MJ\;m^{-2}\;d^{-1}$) for estimates of the daily solar radiation at the weather station in Suwon. The DNN model explained about 68% of variation in observed solar radiation at the Suwon weather station. It was found that the measurements of solar radiation in 1985 and 1998 were considerably low for a small period of time compared with sunshine duration. This suggested that assessment of the quality for the observation data for solar radiation would be needed in further studies. When data for those years were excluded from the data analysis, the DNN model had slightly greater degree of agreement statistics. For example, the values of $R^2$ and RMSE were 0.72 and $3.55MJ\;m^{-2}\;d^{-1}$, respectively. Our results indicate that a DNN would be useful for the development a solar radiation estimation model using temperature and precipitation, which are usually available for downscaled scenario data for future climate conditions. Thus, such a DNN model would be useful for the impact assessment of climate change on crop production where solar radiation is used as a required input variable to a crop model.

• Journal of Environmental Impact Assessment
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• v.28 no.6
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• pp.568-579
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• 2019

The present study aims to identify the effect of land cover categories on particulate matter (PM) concentrations by analyzing the correlation between monthly PM concentrations in Seoul's air quality monitoring network and the percentages of land cover categories by buffers around air quality monitoring stations. According to a monthly correlation analysis between land cover categories and PM concentrations, in the buffer 3km, PM₁₀ showed a better correlation than PM_2.5, there was a clear negative correlation with the forest area, the grassland and the urbanized area had some positive correlation with PM₁₀, and the barren land and the urbanized area had some positive correlation with PM_2.5. According to a monthly correlation analysis of dominant land cover sub-categories and sub-sub-categories within the buffer 3km, PM₁₀ showed a clear negative correlation with the broad-leaved forest, and some positive correlation with the road was dominant. PM_2.5 showed partly negative correlation with the broad-leaved forest and partly positive correlation with the commercial area. There was a very low or no correlation with other grassland and bare land subcategories. A monthly stepwise regression analysis on noticeable land cover sub-categories and sub-sub-categories with positive or negative correlations revealed that an increasing percentage of the broad-leaved forest had a clear effect on reducing PM₁₀ concentrations, and the road was excluded from the selected variables. Although an increasing percentage of the commercial area had some effect on increasing monthly PM_2.5 concentrations and an increasing percentage of the broad-leaved forest had an effect on decreasing the PM_2.5 concentrations, their effect size was smaller than that on PM₁₀. The forest area around the city center had the largest and clearest effect on reducing PM concentrations. The urbanized area's sub-categories and sub-sub-categories were also confirmed to have some effect on increasing PM concentrations.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.4
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• pp.232-237
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• 2010

While global solar radiation is an essential input variable in crop models, the observation stations are relatively sparse compared with other meteorological elements. Instead of using measured solar radiation, the Angstrom-Prescott model estimates have been widely used. Monthly data for solar radiation and sunshine duration are a convenient basis for deriving Angstrom-Prescott coefficients (a, b), but it is uncertain whether daily solar radiation could be estimated with a sufficient accuracy by the monthly data - derived coefficients. We derived the Angstrom-Prescott coefficients from the 25 years observed global solar radiation and sunshine duration data at 18 locations across South Korea. In order to figure out any improvements in estimating daily solar radiation by replacing monthly data with daily data, the coefficients (a, b) for each month were derived separately from daily data and monthly data. Local coefficients for eight validation sites were extracted from the spatially interpolated maps of the coefficients and used to estimate daily solar radiation from September 2008 to August 2009 when, pyranometers were operated at the same sites for validation purpose. Comparison with the measured radiation showed a better performance of the daily data - derived coefficients in estimating daily global solar radiation than the monthly data - derived coefficients, showing 9.3% decrease in the root mean square error (RMSE).

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.1
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• pp.83-91
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• 2014

The occurrence of abnormal sunshine duration was analyzed using meteorological data collected from 60 observation stations during the last 38 years (1973-2010). The 20 agro-climatic zones defined by the Rural Development Administration, were used as a spatial unit for the analysis. On average, abnormal duration of sunshine occurred 1.24 times per year since 1973. The abnormally long duration of sunshine occurred less frequenctly in 2000s (0.47 per year) than in 1970s (1.26 per year). However, the frequency of abnormally short duration of sunshine has increased from an average of 0.58 per year in 1970s to 0.98 in 2000s. The highest frequency of abnormally long duration of sunshine appeared in Central Inland zone with an average of 1.35 frequencies per year. On the other hand, abnormally short duration of sunshine was the most frequent in South Eastern Coastal zone with an average of 0.97 frequencies per year.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.3
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• pp.74-99
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• 2022

Surface ozone is produced by photochemical reactions of nitrogen oxides(NOx) and volatile organic compounds(VOCs) emitted from vehicles and industrial sites, adversely affecting vegetation and the human body. In South Korea, ozone is monitored in real-time at stations(i.e., point measurements), but it is difficult to monitor and analyze its continuous spatial distribution. In this study, surface ozone concentrations were interpolated to have a spatial resolution of 1.5km every hour using the stacking ensemble technique, followed by a 5-fold cross-validation. Base models for the stacking ensemble were cokriging, multi-linear regression(MLR), random forest(RF), and support vector regression(SVR), while MLR was used as the meta model, having all base model results as additional input variables. The results showed that the stacking ensemble model yielded the better performance than the individual base models, resulting in an averaged R of 0.76 and RMSE of 0.0065ppm during the study period of 2020. The surface ozone concentration distribution generated by the stacking ensemble model had a wider range with a spatial pattern similar with terrain and urbanization variables, compared to those by the base models. Not only should the proposed model be capable of producing the hourly spatial distribution of ozone, but it should also be highly applicable for calculating the daily maximum 8-hour ozone concentrations.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.376-385
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• 2018

To estimate the hourly temperature distribution due to solar radiation during the day, on slope in complex terrain, an empirical formula was developed including the hourly deviation in the observed temperature following solar radiation deviation, at weather stations on the east-facing and west-facing slopes. The solar radiation effect was simulated using the empirical formula to estimate hourly temperature at 11 weather observation sites in mountainous agricultural areas, and the result was verified for the period from January 2015 to December 2017. When the estimated temperature was compared with the control, only considering temperature lapse rate, it was found that the tendency to underestimate the temperature from 9 am to 3 pm was reduced with the use of an empirical formula in the form of linear expression; consequently, the estimation error was reduced as well. However, for the time from 5 pm to 6 pm, the estimation error was smaller when a hyperbolic equation drawn from the deviation in solar radiation on the slope, which was calculated based on geometric conditions, was used instead of observed values. The reliability of estimating the daytime temperature at 3 pm was compared with existing estimation model proposed in other studies; the estimation error could be mitigated up to an ME (mean error) of $-0.28^{\circ}C$ and RMSE (root mean square error) of $1.29^{\circ}C$ compared to the estimation error in previous models (ME $-1.20^{\circ}C$, RMSE $2.01^{\circ}C$).

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.5
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• pp.53-65
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• 2022

Most of the reservoirs managed by the city and county are small and it is difficult to respond to climate change because the drainage area is small and the inflow increases rapidly when a heavy rain occurs. In this study, the current status of reservoirs managed by city and county in Gyeonggi-do was reviewed and flood vulnerability due to climate change was analyzed. In order to analyze the impact of climate change, CMIP6-based future climate scenario provided by IPCC was used, and future rainfall data was established through downscaling of climate scenario (SSP8-8.5). The flood vulnerability of reservoirs due to climate change was evaluated using the concept provided by the IPCC. The future annual precipitation at six weather stations appeared a gradual increase and the fluctuation range of the annual precipitation was also found to increase. As a result of calculating the flood vulnerability index, it was analyzed that the flood vulnerability was the largest in the 2055s period and the lowest in the 2025s period. In the past period (2000s), the number of D and E grade reservoirs was 58, but it was found to increase to 107 in the 2055s period. In 2085s, there were 17 E grade reservoirs, which was more than in the past. Therefore, it is necessary to take measures against the increasing risk of flooding in the future.