• Journal of Environmental Impact Assessment
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• v.12 no.4
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• pp.281-290
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• 2003

The influence of land-use type on surrounding temperature was studied the relationships between land-use types and the air condition analyzing AWS (Automatic Weather Station) data of Seoul from KMA (Korea Meteorological Administration). The distribution of air temperature by land-use type has been influenced by the different heating and cooling rates. The difference of heating rates depending on the land-use type was largest at 2~3hours after sunrise and the difference of cooling rates was largest from 2hours before sunset to 2hours after sunset with its maximum at sunset. The difference of cooling rates is greatest in a clear and calm weather situation and the large difference in cooling rates between the green areas and built-up area is up to $1.5^{\circ}C/h$. By season, the difference of cooling rates is largest in fall and in turn spring, winter and summer. In a cloudy or rainy day, the difference in heating and cooling rates on land-use type is not distinct but the tendency is similar to a clear day. In all seasons, the rate of difference occurrence of the daily range of temperature between the green areas and built-up area was large, especially fall. In a fall with a clear and calm day, the magnitude of the daily range of temperature between the green areas and built-up area was largest.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.201-217
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• 2022

The United States is one of the largest producers of major crops such as wheat, maize, and soybeans, and is a major exporter of these crops. Therefore, it is important to estimate the crop production of the country in advance based on reliable long- term weather forecast information for stable crops supply and demand in Korea. The purpose of this study is to improve the seasonal predictability of the agro-climatic indices over the United States by using regional-scale daily temperature. For long-term numerical weather prediction, a dynamical downscaling is performed using Weather Research and Forecasting (WRF) model, a regional climate model. As the initial and lateral boundary conditions of WRF, the global hourly prediction data obtained from the Pusan National University Coupled General Circulation Model (PNU CGCM) are used. The integration of WRF is performed for 22 years (2000-2021) for period from June to December of each year. The empirical quantile mapping, one of the bias correction methods, is applied to the timeseries of downscaled daily mean, minimum, and maximum temperature to correct the model biases. The uncorrected and corrected datasets are referred WRF_UC and WRF_C, respectively in this study. The daily minimum (maximum) temperature obtained from WRF_UC presents warm (cold) biases over most of the United States, which can be attributed to the underestimated the low (high) temperature range. The results show that WRF_C simulates closer to the observed temperature than WRF_UC, which lead to improve the long- term predictability of the temperature- based agro-climatic indices.

• Atmosphere
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• v.21 no.4
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• pp.361-371
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• 2011

In this study, characteristics and trends of tropical night (TN) are investigated by using the KMA 14 observation data for the recent 50 years (1958-2007) over South Korea. The TN is defined as a day with a daily minimum temperature exceeds the absolute threshold temperature ($25^{\circ}C$), and the relative deviation from normal temperature, 95th percentile of all observed daily minimum temperature. Although the spatial distribution of TN occurrence depends on the choice of the definitions, the frequency of TN shows strong spatial and interannual variations with the minimum at high land area (Chupungnyeong and wet years) and maximum at southern coastal area and large city area (Jeju, Busan, Seoul, Daegu). Most of TN occurs in August (56%) and July (41%), and the duration date of TN is proportional to the frequency of TN without regard to the definition method. In general, increasing trends are found in the TN time series without regard to the analysis method, but the trends are clearly depending on the analysis period and geographic locations. Decreasing trends are prominent during the most of analysis period, especially until the mid of 1990, whereas strong increasing trends are found during recent 30 years (1988-2007), especially at Jeju, Ulsan, Daegu and Pohang. Also the severity of TN is significantly increased in recent years.

• Water Engineering Research
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• v.4 no.3
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• pp.111-126
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• 2003

Meteorological data are often needed to evaluate the long-term effects of proposed hydrologic changes. The evaluation is frequently undertaken using deterministic mathematical models that require daily weather data as input including precipitation amount, maximum and minimum temperature, relative humidity, solar radiation and wind speed. Stochastic generation of the required weather data offers alternative to the use of observed weather records. The precipitation is modeled by a Markov Chain-exponential model. The other variables are generated by multivariate model with means and standard deviations of the variables conditioned on the wet or dry status of the day as determined by the precipitation model. Ultimately, the objective of this paper is to compare Richardson's model and the improved weather generation model in their ability to provide daily weather data for the crop model to study potential impacts of climate change on the irrigation needs and crop yield. However this paper does not refer to the improved weather generation model and the crop model. The new weather generation model improved will be introduced in the Journal of KWRA.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.151-151
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• 2018

The present study is aimed to quantifying the uncertainty in the general circulation model (GCM) selection and its impacts on hydrology studies in the basins. For this reason, 13 GCMs was selected among the 26 GCM models of the Fifth Assessment Report (AR5) scenarios. Then, the climate data and hydrologic data with two Representative Concentration Pathways (RCPs) of the best model (INMCM4) and worst model (HadGEM2-AO) were compared to understand the uncertainty associated with GCM models. In order to project the runoff, the Precipitation-Runoff Modelling System (PRMS) was driven to simulate daily river discharge by using daily precipitation, maximum and minimum temperature as inputs of this model. For simulating the discharge, the model has been calibrated and validated for daily data. Root mean square error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were applied as evaluation criteria. Then parameters of the model were applied for the periods 2011-2040, and 2070-2099 to project the future discharge the five large basins of South Korea. Then, uncertainty caused by projected temperature, precipitation and runoff changes were compared in seasonal and annual time scale for two future periods and RCPs compared to the reference period (1976-2005). The findings of this study indicated that more caution will be needed for selecting the GCMs and using the results of the climate change analysis.

• Journal of fish pathology
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• v.26 no.3
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• pp.173-183
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• 2013

From July to early September 2012, there was mass mortality of fishes, particularly black rockfish, which were being raised in the floating fish cage along the coast of Gyeongsangnam-do. The amount of damage was 1,802,000 fishes and the causes were confirmed to be rapidly rising water temperature and repeated daily changes in water temperature. The water temperature in this area of the sea rose to the maximum $28.4^{\circ}C$ and the daily range of changes in water temperature was maximum $6.5^{\circ}C$. As a result of investigating biological diseases of 194 fishes in 49 fishery areas, major pathogenic organisms such as red seabream iridovirus (RSIV), Vibrio sp. and Vibrio spp. or Microcotyle sp. were detected in rockfish in some fish farms. It is considered that the major causes of the mass mortality were high water temperature accompanied by repeated daily changes in water temperature, it is considered that biological diseases influenced the increase in the perish of fishes.

• Horticultural Science & Technology
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• v.31 no.5
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• pp.538-543
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• 2013

During summer in Korea, the excessively high temperature causes growth retardation and quality reduction in cut roses grown in greenhouse. Mist treatments were conducted to reduce the temperature and avoid quality reduction of cut roses. The temperature change in the greenhouse, growth and quality of cut roses, and injuries caused by insects or fungi were investigated during mist treatment. Daily maximum temperature reduced as the number of mist treatment increased, resulting in $6^{\circ}C$ reduction by mist treatment for 10 seconds at 5 min interval. This temperature reduction occurred only when maximum temperature was over $40^{\circ}C$ in greenhouse, and not when it was less than $40^{\circ}C$ or rainy and/or cloudy day. Plant height and fresh weight of the cut roses were increased at the range of 10-20% by mist treatment. As frequency of mist treatment increased, however, malformed flowers increased and vase life of cut rose was largely shortened. The injuries by insects like as beet armyworm larvae and scale insect increased as well. In conclusion, it is recommended that mist treatment must be used when the daily maximum temperature in a green house is over $40^{\circ}C$ and forecasting for disease or insects should be conducted as well.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.62 no.4
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• pp.304-310
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• 2017

This study was conducted over a 3-year period from 2013 to 2015 in the mid-northern inland, Cheolweon, Korea, to investigate changes in flowering date, daily mean temperature during grain filling, and yield characteristics affected by transplanting date in an early-maturing rice variety, 'Joun'. Thirty-day-old seedlings were transplanted at four different dates at 15-day interval from May 5 to June 19. Flowering dates were July 16, July 21, July 31, and August 14 when transplanting was performed on May 5, May 20, June 4, and June 19, respectively. Late transplanting resulted in higher daily mean temperature before flowering but late-transplanted rice required fewer days and lower cumulative temperature to reach flowering from transplanting. As transplanting was delayed, daily mean temperature for 40 days after flowering decreased, whereas daily sunshine hours for the same period increased, with a temperature of $24.8^{\circ}C$ and sunshine for 5.8 hours being recorded at the transplanting on May 5, and with a temperature of $21.0^{\circ}C$ and sunshine for 7.7 hours at the transplanting on June 19. With late transplanting, panicles per square meter significantly decreased, whereas spikelets per panicle showed an increasing trend. Regression analysis showed that maximum head rice yield was attained from the transplanting on May 18, for which the flowering date was July 21, and daily mean temperature for 40 days from that flowering date was $24.6^{\circ}C$. A decrease in head rice yield by 5% and 10% of the maximum was observed for rice transplanted on June 6 and June 15, which resulted in flowering dates of August 2 and August 11, respectively, and the daily mean temperatures for 40 days from flowering were 23.2 and $21.7^{\circ}C$, respectively. Therefore, in mid-northern inland, it is recommended to transplant 'Joun' on May 18 to induce flowering on July 21, when grain filling is subjected to a daily mean temperature of $24.6^{\circ}C$ during active filling stage.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.6
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• pp.87-99
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• 2013

For analysis of climate change effects on agriculture, precise agricultural meteorological data are needed to target period and site. In this study, agricultural meteorological data under new climate change scenario (RCP 8.5) are constructed from 2011 to 2099 in 111 agriculture major station suggested by Rural Development Administration (RDA). For verifying constructed data, comparison with field survey data in Suwon shows same trend in maximum temperature, minimum temperature, average temperature, and precipitation in 2011. Also comparison with normals of daily data in 2025, 2055, and 2085 shows reliability of constructed data. In analysis of constructed data, we can calculate sum of days over temperature and under temperature. Results effectively show the change of average temperature in each region and odd days of precipitation which means flood and dry days in target region.

• The Korean Journal of Applied Statistics
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• v.20 no.1
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• pp.1-9
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• 2007

This investigation on the change of the daily maxima temperature in Seoul, Daegu, Chunchen, Youngchen was triggered by news items such as the earth is getting warmer and a recent news item that said that Korea is getting warmer due to this climatic change. A statistical analysis on the daily maxima for June over this period in Seoul revealed a positive trend of 1.1190 centigrade over the 45 years, a change of 0.0249 degrees annually. Due to the large variation on these maximum temperatures, one can raise the question on the significance of this increase. To check the goodness of fit of the proposed extreme value model, we shown a Q-Q plot of the observed quantiles against the simulated quantiles and a probability plot. And we calculated statistics each month and a tolerance limit. This is tested through simulating a large number of similar datasets from an Extreme Value distribution which described the observed data very well. Only 0.02% of the simulated datasets showed an increase of this degrees or larger, meaning that the probability is very low for such an event to occur.