• Journal of Environmental Science International
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• v.19 no.10
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• pp.1237-1246
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• 2010

This paper aims to analyze the perception of university students for the extreme heat watch warning and suggest the usefulness of special weather reports. For this, we have made up a descriptive questionnaires including the perception, mass media, usefulness and satisfaction of special weather report. Using the SPSS 17.0 program, descriptive statistics, t-test, ANOVA and Scheffe test were used to analyze the collected data. The result are as follows; The perception of extreme heat watch warning was some low as 59.1 percentile, we think it needs education and public relations about the extreme heat watch warning. The usefulness of special weather report was 66.6 percentile and of girl students of university that was educated about health care was higher than one of boy students of university, it needs continuous education of these students in order to upgrade satisfaction of special report and mitigate the hazard of extreme heat according to climate change. The main media to get the meteorological information of university undergraduate students were TV and Internet, it needed education and development of new contents. From these findings, suggestions are presented to help improve the extreme heat watch warning.

• Journal of Environmental Science International
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• v.17 no.6
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• pp.657-669
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• 2008

Lately extreme weather event is occurring because of the global warming. Especially disaster due to the extreme heat are increasing but the definition and the standard of the extreme heat is obscure until now. So this study established the extreme heat standard by using the number of daily deaths. As a result, considering the climate of the megalopolis using daily maximum heat index and daily maximum temperature was the best for the standard of the extreme heat. And it showed that extreme heat lasted for 2 days affects the death toll the most. The regional incidence of the extreme heat is highest at August and July, September and June is following.

• Atmosphere
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• v.23 no.3
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• pp.347-356
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• 2013

The climate projection with a high spatial resolution is required for the studies on regional climate changes. The Korea Meteorological Administration (KMA) has provided downscaled RCP (Representative Concentration Pathway) scenarios over Korea with 1 km spatial resolution. If there are additional climate projections produced by dynamically downscale, the quality of impacts and vulnerability assessments of Korea would be improved with uncertainty information. This technical note intends to instruct the methods to downscale the climate projections dynamically from the Community Earth System Model (CESM) to the Weather Research and Forecast (WRF) model. In particular, here we focus on the instruction to utilize CAM2WRF, a sub-program to link output of CESM to initial and boundary condition of WRF at Linux platform. We also provide the example of the dynamically downscaled results over Korean Peninsula with 50 km spatial resolution for August, 2020. This instruction can be helpful to utilize global scale climate scenarios for studying regional climate change over Korean peninsula with further validation and uncertainty/bias analysis.

• Korean Journal of Remote Sensing
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• v.24 no.1
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• pp.45-55
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• 2008

The impact on streamflow and groundwater recharge considering future potential climate and land use change was assessed using SLURP (Semi-distributed Land-Use Runoff Process) continuous hydrologic model. The model was calibrated and verified using 4 years (1999-2002) daily observed streamflow data for a $260.4km^2$ which has been continuously urbanized during the past couple of decades. The model was calibrated and validated with the coefficient of determination and Nash-Sutcliffe efficiency ranging from 0.8 to 0.7 and 0.7 to 0.5, respectively. The CCCma CGCM2 data by two SRES (Special Report on Emissions Scenarios) climate change scenarios (A2 and B2) of the IPCC (Intergovemmental Panel on Climate Change) were adopted and the future weather data was downscaled by Delta Change Method using 30 years (1977 - 2006, baseline period) weather data. The future land uses were predicted by CA (Cellular Automata)-Markov technique using the time series land use data of Landsat images. The future land uses showed that the forest and paddy area decreased 10.8 % and 6.2 % respectively while the urban area increased 14.2 %. For the future vegetation cover information, a linear regression between monthly NDVI (Normalized Difference Vegetation Index) from NOAA/AVHRR images and monthly mean temperature using five years (1998 - 2002) data was derived for each land use class. The future highest NDVI value was 0.61 while the current highest NDVI value was 0.52. The model results showed that the future predicted runoff ratio ranged from 46 % to 48 % while the present runoff ratio was 59 %. On the other hand, the impact on runoff ratio by land use change showed about 3 % increase comparing with the present land use condition. The streamflow and groundwater recharge was big decrease in the future.

• Korean Journal of Environmental Agriculture
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• v.33 no.1
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• pp.52-56
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• 2014

BACKGROUND: It is known that impacts of climate change on damage occurrence by insect pests and diseases are increasing. The negative effects of climate change on production will threaten our food security. It is needed that on the basis of analysis of the impacts, proper strategies in response to climate change are developed. METHODS AND RESULTS: The objective of this paper is to estimate impacts of climate change on rice damage occurrence by insect pests and diseases, using the panal model which analyzes both cross-section data and time series data. The result of an analysis on impacts of climate change on rice damage occurrence by pest insect and disease showed that the damage occurrence by Rice leaf roller and Rice water weevil increased if temperature increased, and damage occurrence by Stripe, Sheath blight, and Leaf Blast increased if precipitation(or amount of sunshine) increased(or decreased). CONCLUSION: Adaptation strategies, supplying weather forecasting information by region, developing systematical strategies for prevention of damage occurrence by pest insect and disease, analyzing the factors of damage occurrence by unexpected pest insect and disease, enforcing international cooperation for prevention of damage occurrence are needed to minimize the impacts of damage occurrence on rice production.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.1
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• pp.1-10
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• 2010

A regional climate model (RCM) can be a powerful tool to enhance spatial resolution of climate and weather information (IPCC, 2001). In this study we conducted dynamical downscaling using Weather Research and Forecasting Model (WRF) as a RCM in order to obtain high resolution regional agroclimate indices over the Korean Peninsula. For the purpose of obtaining detailed high resolution agroclimate indices, we first reproduced regional weather for the period of March to June, 2002-2008 with dynamic downscaling method under given lateral boundary conditions from NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis data. Normally, numerical model results have shown biases against observational results due to the uncertainties in the modelis initial conditions, physical parameterizations and our physical understanding on nature. Hence in this study, by employing a statistical method, the systematic bias in the modelis results was estimated and corrected for better reproduction of climate on high resolution. As a result of the correction, the systematic bias of the model was properly corrected and the overall spatial patterns in the simulation were well reproduced, resulting in more fine-resolution climatic structures. Based on these results, the fine-resolution agro-climate indices were estimated and presented. Compared with the indices derived from observation, the simulated indices reproduced the major and detailed spatial distributions. Our research shows a possibility to simulate regional climate on high resolution and agro-climate indices by using a proper downscaling method with a dynamical weather forecast model and a statistical correction method to minimize the model bias.

• Proceedings of KOSOMES biannual meeting
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• 2017.11a
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• pp.242-242
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• 2017

• Journal of Environmental Science International
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• v.23 no.1
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• pp.25-37
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• 2014

In the present study, we analyzed precipitation patterns and diurnal variation trends of hourly precipitation intensity due to climate change. To that end, we used the hourly precipitation data obtained from 26 weather stations around South Korea, especially Busan, from 1970 to 2009. The results showed that the hourly precipitation was concentrated on a specific time of day. In particular, the results showed the so-called "morning shift" phenomenon, which is an increase in the frequency and intensity of hourly precipitation during the morning. The morning shift phenomenon was even more pronounced when a higher level of hourly precipitation intensity occurred throughout the day. Furthermore, in many regions of Korea, including Busan, this morning shift phenomenon became more prevalent as climate change progressed.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.4
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• pp.304-311
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• 2013

There have been increasing cases for farmers to install automated weather stations (AWS) at their farms and orchards in order to take countermeasures to more frequent weather disasters caused by climate variability and weather extremes. Although raw data are the same, the additive values as agrometeorological information may vary depending on data processing methods. User demands on appropriate information could also be different among crop species, cropping systems and even cultivars. We designed an internet based AWS data processing and display system to help diverse users (e.g., farmers), extension workers to access their weather data on specific demands. The system was implemented at a rural catchment with 52 $km^2$ land area where 14 automated weather stations are in operation. This note introduces the system and describes the major modules in detail. By linking regional AWS networks, a feasibility for this system as an early warning system is also discussed.

• Environmental Engineering Research
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• v.18 no.1
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• pp.9-20
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• 2013

In this paper, the rainfall elasticity of streamflow was estimated to quantify the effects of climate change on 5 river basins. Rainfall elasticity denotes the sensitivity of annual streamflow for the variations of potential annual rainfall. This is a simple, useful method that evaluates how the balance of a water cycle on river basins changes due to long-term climate change and offers information to manage water resources and environment systems. The elasticity method was first used by Schaake in 1990 and is commonly used in the United States and Australia. A semi-distributed hydrological model (SLURP, semi-distributed land use-based runoff processes) was used to simulate the variations of area streamflow, and potential evapotranspiration. A nonparametric method was then used to estimate the rainfall elasticity on five river basins of Korea. In addition, the A2 (SRES IPCC AR4, Special Report on Emission Scenarios IPCC Fourth Assessment Report) climate change scenario and stochastic downscaling technique were used to create a high-resolution weather change scenario in river basins, and the effects of climate change on the rainfall elasticity of each basin were then analyzed.