• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.5
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• pp.91-99
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• 2016

High resolution rainfall data at 1-hour or a finer scale are essential for reliable flood analysis and forecasting; nevertheless, many observations, forecasts, and climate projections are still given at coarse temporal resolutions. This study aims to evaluate a chaotic method for disaggregation of 6-hour rainfall data sets so as to apply operational 6-hour rainfall forecasts of the Korean Meteorological Association to flood models. We computed parameters of a state-of-the-art multiplicative random cascade model with two combinations of cascades, namely uniform splitting and diversion, using rainfall observations at Seoul station, and compared statistical performance. We additionally disaggregated 6-hour rainfall time series at 58 stations with the uniform splitting and evaluated temporal transferability of the parameters and changes in multifractal properties. Results showed that the uniform splitting outperformed the diversion in reproduction of observed statistics, and hence is better to be used for disaggregation of 6-hour rainfall forecasts. We also found that multifractal properties of rainfall observations has adequate temporal consistency with an indication of gradually increasing rainfall intensity across South Korea.

• 한국태양에너지학회:학술대회논문집
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• 2009.04a
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• pp.180-183
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• 2009

In this study, Urban Climate Simulation was performed by 3-Dimensional Urban Canopy Model. The characteristics of urban climate was analyzed combining artificial land coverage, building size, heat production from the air conditioning and topographic conditions as physical variables which affects urban climate characteristics. The results are as follows. (1)The aspects of the urban climatal change is derived to be related to the combination of the building coverage ratio, building height and shading area. (2)Whole heat generation was influenced by the convective sensible heat at the lower building height and by the artificial heat generation at the higher one over 20-story building influence to some extent of the building coverage ratio. The effect of the altitude is not more considerable than the other variables as below $1^{\circ}C$ of the air temperature.

• Atmosphere
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• v.18 no.1
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• pp.33-41
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• 2008

This study provides an impact assesment of climate change on energy consumption, based on active-deal scenario. This approach assumes that the amount of electric energy consumption depends on human spontaneous acts against local (REC) has ben developed by using monthly mean temperature and monthly amount of electric energy consumption in the 6 major cities over the 19-205 period. The statistical model is utilized to estimate the past and future REEC, and to assess the economic benefits and damage in energy consumption sector. For an estimation of the future REEC, climate change scenario, which is generated by National Institute of Meteorological Research, is utilized in this study. According to the model, it is estimated that over the standard period (1999~2005), there might be economic benefits of about 31 bilion Won/year in Seoul due to increasing temperature than in the 1980s. The REC is also predicted to be gradually reduced across the Korean peninsula since the 2020s. These results suggest that Korea will gain economic benefits in the REC sector during the 21st century as temperature increases under global warming scenarios.

• Atmosphere
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• v.16 no.3
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• pp.215-223
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• 2006

Among observational, local-environmental, and large-scale factors causing significant changes in climate records, the site relocations and the replacement of the instruments are well-known nonclimatic factors for the analysis of climatic trends, climatic variability, and for the detection of anthropogenic climate change such as heat-island effect and global warming. Using dataset that were contaminated by these nonclimatic factors can affect seriously the assessment of climatic trends and variability, and the detection of the climatic change signal. In this paper, the inhomogeneities, which have been caused by relocation of the observation site, in the climate data of Korea Meteorological Administration (KMA) were examined using two-phase regression model. The observations of pan evaporation and wind speed are more sensitive to site relocations than those of other meteorological elements, such as daily mean, maximum and minimum temperatures, with regardless to region.

• Atmosphere
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• v.22 no.3
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• pp.331-344
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• 2012

The changes in the Hadley circulation during the second half of the 20th century were examined using observations and the 20C3M (Twentieth Century Climate in Coupled Models) simulations by the 21 IPCC AR4 models. Multi-model ensemble (MME) mean shows that the mean features of the Hadley circulation, such as the intensity, magnitude, and the seasonal variations, are very realistically reproduced, compared to the ERA40 reanalysis. But the long-term trends of the Hadley circulation in 20C3M MME are quite different to those of observations. The observed intensity of the Hadley cell is persistently enhanced, particularly during boreal winter. In comparison, the meridional overturning circulations reproduced in the MME mean remains invariant in time, and even weakened in boreal summer. This discrepancy between the ERA40 and 20C3M MME is consistently shown in the overall structure of the Hadley circulations, such as mass streamfunction, the velocity potential, the vertical shear of meridional wind, and the vertical velocity in the tropical region. This results indicate that the current climate models are skill-less to capture the long-term trend of Hadley circulation yet, and should be improved in simulation of the large-scale features to enhance the confidence level of future climate change projection.

• Journal of the Korean Geographical Society
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• v.51 no.5
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• pp.633-649
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• 2016

Exposure to high temperatures during the reproductive period of crops decreases their productivity. The Intergovernmental Panel on Climate Change's (IPCC) fifth Assessment Report predicts that the frequency of high temperatures will continue to increase in the future, resulting in significant impacts on the world's food supply. This study evaluate climate change-induced heat stress on four major agricultural crops (rice, maize, soybean, and wheat) at a global level, using the coupled atmosphere-ocean model of Hadley Centre Global Environmental Model version 2 (HadGEM2-AO) and FAO/IIASA Global Agro-Ecological Zone (GAEZ) model data. The maximum temperature rise ($1.8-3.5^{\circ}C$) during the thermal-sensitive period (TSP) from the baseline (1961-1990) to the future (2070-2090) is expected to be larger under a Representative Concentration Pathway (RCP) 8.5 climate scenario than under a RCP2.6 climate scenario, with substantial heat stress-related damage to productivity. In particular, heat stress is expected to cause severe damage to crop production regions located between 30 and $50^{\circ}N$ in the Northern Hemisphere. According to the RCP8.5 scenario, approximately 20% of the total cultivation area for all crops will experience unprecedented, extreme heat stress in the future. Adverse effects on the productivity of rice and soybean are expected to be particularly severe in North America. In Korea, grain demands are heavily dependent on imports, with the share of imports from the U.S. at a particularly high level today. Hence, it is necessary to conduct continuous prediction on food security level following the climate change, as well as to develop adaptation strategy and proper agricultural policy.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.2
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• pp.228-232
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• 2018

Process-based crop models have been used to assess the impact of climate change on crop production. These models are implemented in procedural or object oriented computer programming languages including FORTRAN, C++, Delphi, Java, which have a stiff learning curve. The requirement for a high level of computer programming is one of barriers for efforts to develop and improve crop models based on biophysical process. In this study, we attempted to develop a Chinese cabbage model using Microsoft Excel with Visual Basic for Application (VBA), which would be easy enough for most agricultural scientists to develop a simple model for crop growth simulation. Results from Soil-Plant-Atmosphere-Research (SPAR) experiments under six temperature conditions were used to determine parameters of the Chinese cabbage model. During a plant growing season in SPAR chambers, numbers of leaves, leaf areas, growth rate of plants were measured six times. Leaf photosynthesis was also measured using LI-6400 Potable Photosynthesis System. Farquhar, von Caemmerer, and Berry (FvCB) model was used to simulate a leaf-level photosynthesis process. A sun/shade model was used to scale up to canopy-level photosynthesis. An Excel add-in, which is a small VBA program to assist crop modeling, was used to implement a Chinese cabbage model under the environment of Excel organizing all of equations into a single set of crop model. The model was able to simulate hourly changes in photosynthesis, growth rate, and other physiological variables using meteorological input data. Estimates and measurements of dry weight obtained from six SPAR chambers were linearly related ($R^2=0.985$). This result indicated that the Excel/VBA can be widely used for many crop scientists to develop crop models.

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.3
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• pp.209-218
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• 2024

The National Institute of Agricultural Sciences (NAS) operates in-house long-range climate forecasting system to support the agricultural use of climate forecast data. This system, developed through collaborative research with Pusan National University, is based on the PNU/RDA Coupled General Circulation Model (CGCM) and includes the regional climate model WRF (Weather Research and Forecasting). It generates detailed climate forecast data for periods ranging from 1 to 6 months, covering 20 key variables such as daily maximum, minimum, and average temperatures, precipitation, and agricultural meteorological elements like solar radiation, soil moisture, and ground temperature-factors essential for agricultural forecasting. The data are provided at a daily temporal resolution with a spatial resolution of a 5km grid, which can be used in point form (interpolated) or averaged across administrative regions. The system's seasonal temperature and precipitation forecasts align closely with observed climatological data, accurately reflecting spatial and topographical influences, confirming its reliability. These long-range forecasts from NAS are expected to offer valuable insights for agricultural planning and decision-making. The detailed forecast data can be accessed through the Climate Change Assessment Division of NAS.

• International Journal of Concrete Structures and Materials
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• v.11 no.2
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• pp.199-213
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• 2017

Chloride penetration is among the main causes of corrosion initiation in reinforced concrete (RC) structures producing premature degradations. Weather and exposure conditions directly affect chloride ingress mechanisms and therefore the operational service life and safety of RC structures. Consequently, comprehensive chloride ingress models are useful tools to estimate corrosion initiation risks and minimize maintenance costs for RC structures placed under chloride-contaminated environments. This paper first presents a coupled thermo-hydro-chemical model for predicting chloride penetration into concrete that accounts for realistic weather conditions. This complete numerical model takes into account multiple factors affecting chloride ingress such as diffusion, convection, chloride binding, ionic interaction, and concrete aging. Since the complete model could be computationally expensive for long-term assessment, this study also proposes model simplifications in order to reduce the computational cost. Long-term chloride assessments of complete and reduced models are compared for three locations in France (Brest, Strasbourg and Nice) characterized by different weather and exposure conditions (tidal zone, de-icing salts and salt spray). The comparative study indicates that the reduced model is computationally efficient and accurate for long-term chloride ingress modeling in comparison to the complete one. Given that long-term assessment requires larger climate databases, this research also studies how climate models may affect chloride ingress assessment. The results indicate that the selection of climate models as well as the considered training periods introduce significant errors for mid- and long- term chloride ingress assessment.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.4
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• pp.55-64
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• 2021

The expansion of upland crop cultivation in rice paddy fields is recommended by the Korean government to solve the problem of falling rice price and reduction of rice farmer's income due to oversupply of rice. However, water use efficiency is significantly influenced by the land use change from paddy field to upland. Therefore, this study aimed to evaluate the water budget of soybean grown in using APEX (Agricultural Policy and Environmental eXtender) model. The amount of runoff was measured in a test bed located in Iksan, Jeollabu-do and used to calibrate and validate the simulated runoff by APEX model. From 2019 to 2020, the water budget of soybean grown in uplands were estimated and compared with the one grown in paddy fields. The calibration result of AP EX model for runoff showed that R² (Coefficient of determination) and NSE (Nash-Sutcliffe efficiency) were 0.90 and 0.89, respectively. In addition, the validated results of R² and NSE were 0.81 and 0.62, respectively. The comparative study of each component in water budget showed that the amounts of evapotranspiration and percolation estimated by APEX model were 549.1 mm and 375.8mm, respectively. The direct runoff amount from upland was 390.1 mm, which was less than that from paddy fields. The average amount of irrigation water was 28.7 mm, which was very small compared to the one from paddy fields.