• Journal of Climate Change Research
• /
• v.6 no.2
• /
• pp.133-142
• /
• 2015

The purpose of this study was to compare the results of climate change prospect and vulnerability assessment and the awareness of those by public officials and citizens at Yeongwol county, Gangwon province where experiencing the most climate change vulnerability. Data of 12 meteorological categories such as mean temperature at Yeongwol weather station from 1995 to 2013 were analyzed. Climate change vulnerability was assessed with 29 sub-categories in 6 categories (health, emergency/disaster, agriculture, forestry, water management, ecosystem) of National Institute of Environment Research's LCCGIS (2013). The awareness of climate change and its vulnerability was surveyed with 154 citizens and 130 officials at Yeoungwol county. The climate change prospect and its vulnerability was similar to the actual climate change effect. However, the awareness of climate change was different between some officials and citizens. The results of this study would be base data for the Yeoungwol county's future climate change adaptation poicy making.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.59 no.3
• /
• pp.29-39
• /
• 2017

In this study, the GPM (Global Precipitation Mission) IMERG (Integrated Multi-satellitE retrievals for GPM) rainfall data was verified and evaluated using ground AWS (Automated Weather Station) and radar in order to investigate the availability of GPM IMERG rainfall data. The SPI (Standardized Precipitation Index) was calculated based on the GPM IMERG data and also compared with the results obtained from the ground observation data for the Hoengseong Dam and Yongdam Dam areas. For the radar data, 1.5 km CAPPI rainfall data with a resolution of 10 km and 30 minutes was generated by applying the Z-R relationship ($Z=200R^{1.6}$) and used for accuracy verification. In order to calculate the SPI, PERSIANN_CDR and TRMM 3B42 were used for the period prior to the GPM IMERG data availability range. As a result of latency verification, it was confirmed that the performance is relatively higher than that of the early run mode in the late run mode. The GPM IMERG rainfall data has a high accuracy for 20 mm/h or more rainfall as a result of the comparison with the ground rainfall data. The analysis of the time scale of the SPI based on GPM IMERG and changes in normal annual precipitation adequately showed the effect of short term rainfall cases on local drought relief. In addition, the correlation coefficient and the determination coefficient were 0.83, 0.914, 0.689 and 0.835, respectively, between the SPI based GPM IMERG and the ground observation data. Therefore, it can be used as a predictive factor through the time series prediction model. We confirmed the hydrological utilization and the possibility of real time drought monitoring using SPI based on GPM IMERG rainfall, even though results presented in this study were limited to some rainfall cases.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.42 no.4
• /
• pp.780-784
• /
• 2017

Data discovery and distribution application that is utilized by climate, high energy physics, and other scientific communities are experiencing performance and large scale data managing problems, that are rooted from the shortcomings of IP architecture. To solve this problem, newly developed data managing applications based on NDN architecture were introduced. In this letter, we present the federated NDN testbed with an NDN-based climate science application and the set of experiments that reflect the performance of NDN based climate application in general with determined and applied optimization.

• Journal of Korean Society on Water Environment
• /
• v.25 no.6
• /
• pp.863-871
• /
• 2009

For the assessment of climate change impacts on river flow condition, CGCM 3.1 T63 is selected as future climate information. The projections come from CGCM used to simulate the GHG emission scenario known as A2. Air temperature and precipitation information from the GCM simulations are converted to regional scale data using the statistical downscaling method known as MSPG. Downscaled climate data from GCM are then used as the input data for the modified TANK model to generate regional runoff estimates for 44 river locations in Nakdong river basin. Climate change is expected to reduce the reliability of water supplies in the period of 2021~2030. In the period of 2051~2060, stream flow is expected to be reduced in spring season and increased in summer season. However, it should be noted that there are a lot of uncertainties in such multiple-step analysis used to convert climate information from GCM-based future climate projections into hydrologic information.

• Atmosphere
• /
• v.17 no.4
• /
• pp.483-492
• /
• 2007

The objective of this study is to describe scientific progresses in understanding of climate change in the Intergovernmental Panel on Climate Change (IPCC) assessment reports, contributed by Working group I. Since 1988, IPCC's four assessment reports showed significant improvements in understanding of observed climate change, drivers of climate change, detection and attribution of climate change, climate models, and future projection. The results are based on large amounts of observation data, sophisticated analyses of data, improvements of climate models and the simulations. While the First Assessment Report (FAR) in 1990 reported that a detectable anthropogenic influence on climate has little observational evidence, the Fourth Assessment Report (AR4) reported that warming of the climate system is unequivocal and is very likely due to human influences. It is also noted that anthropogenic warming and sea level rise would continue for centuries due to the time scales associated with climate processes and feedbacks, even if greenhouse gas were to be stabilized.

• Atmosphere
• /
• v.25 no.2
• /
• pp.205-219
• /
• 2015

In this study, the simulation results of temperature by regional climate model (Reg- CM4) over South Korea were corrected by Hempel et al. (2013)'s method (Hempel method), and evaluated with the observation data of 50 stations from Korea Meteorological Administration. Among the 30 years (1981~2010) of simulation data, 20 years (1981~2000) of simulation data were used as a training data, and the remnant 10 years (2001~2010) data were used for the evaluation of correction. In general, the Hempel method and parametric quantile mapping show a reasonable correction both in mean and extreme climate of temperature. As the results, the systematic underestimation of mean temperature was greatly reduced after bias correction by Hempel method. And the overestimation of extreme climate, such as the number of TN5% and freezing day, was significantly recovered. In addition to that, the Hempel method better preserved the temporal trend of simulated temperature than other bias correction methods, such as the quantile mapping. However, the overcorrection of the extreme climate related to the upper quantile, such as TX5% and hot days, resulted in the exaggeration of the simulation errors. In general, the Hempel method can reduce the systematic biases embedded in the simulation results preserving the temporal trend but it tends to overcorrect the non-linear biases, in particular, extreme climate related to the upper percentile.

• Human Ecology Research
• /
• v.61 no.4
• /
• pp.599-613
• /
• 2023

This study investigated female consumers' attitudes toward the general and fashion-specific climate environments and analyzed the relations between the attitudes and the variables such as values, knowledge, and climate cognition. The data was collected from a sample of 450 women in their 20s, 30s, and 40s via quota sampling from a selfreported online survey in 2023. The measurement comprised the attitudes toward the general and fashion-specific climate environments, Rokeach's 18 terminal values, Holbrook's 8 consumer values regarding fashion products, climate environmental knowledge related to fashion, the cognition concerning the climate crisis, and several demographic variables. Descriptive statistics, factor analysis, reliability analysis, and correlations were applied to the data using SPSS. As a result, two factors were determined for the attitudes toward the general and fashion-specific climate environments, respectively: social and personal. Family security, happiness, and self-respect were identified as important terminal values. Quality, efficiency, aesthetics, and ethics were considered important when the current sample group purchased fashion products. The mean score of climate environmental knowledge related to fashion was lower than neutral; however the cognition of the climate crisis was considerably high. Attitudes toward the general and fashion-specific climate environments showed positive relations with values, knowledge, and climate cognition. The results were discussed to provide some insight and suggestions to carbon neutrality and the related studies.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2010.04a
• /
• pp.383-385
• /
• 2010

This study analyzed the change of flowout and suspend solid in Andong and Imha basin according to the climate change to develop evaluation index about turbid water occurrence possibility and to support the countermeasures for turbid water management using GIS-based Soil and Water Assessment Tools (SWAT). MIROC3.2 hires model values of A1B climate change scenario that were supplied by Intergovernmental Panel on Climate Change (IPCC) were applied to future climage change data. Precipitation and temperature were corrected by applying the output value of 20th Century Climate Coupled Model (20C3M) based on past climate data during 1977 and 2006 and downscaled with Change Factor (CF) method. And future climate change scenarios were classified as three periods (2020s, 2050s, 2080s) and the change of flowout and suspended solid according to the climate change were estimated by coupling modeled value with SWAT model.

• Atmosphere
• /
• v.23 no.2
• /
• pp.237-243
• /
• 2013

A set of scripts for GrADS (Grid Analysis and Display System) and R was implemented to produce agricultural climate information using the future climate scenarios based on the Representative Concentration Pathways. The GrADS script was used to calculate agricultural climate indices including growing degree days and cooling degree days. The script generated agricultural climate maps of these indices, which are compatible with common Geographic Information System (GIS) applications. To perform a statistical analysis using the agricultural climate maps, a script for R, which is open source statistical software, was used. Because a large number of spatial climate data were produced, parallel processing packages such as SNOW, doSNOW, and foreach were used to perform a simple statistical analysis in the R script. The parallel script of R had speedup on workstations with multi-CPU cores.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
• /
• 2019.08a
• /
• pp.195-196
• /
• 2019