• 한국환경과학회지
• /
• 제1권1호
• /
• pp.29-39
• /
• 1992

A study on acidity in precipitation was carried out during May 1990 - April 1991 at two sites in Chongwon, Choongbook. We observed variations of pH from 4.0 to 7.0. Annual mean value of pH was 5.21 in the area. In particular, strong acidity of rain fall, pH 4.0 were observed during winter to early spring. Neutral values were observed during June to July and were due to wet deposition of atmospheric pollutants by stationary fronts in the rainy season. Interestingly, acidity of snow observed in winter was neutral and it was weaker than the acidity of rain in winter by a value of 2.0. Discussion is made on meteorological and chemical analyses and seasonal variations of acidity of precipitation.

• 물과 미래
• /
• 제11권2호
• /
• pp.62-69
• /
• 1978

Interstational and interseasonal analyses of the correlation and variability in the seasonal and annual precipitation for 10 basic synoptic stations in South Korea, on the basis of rainfall record of over 40 years, are carried out. It is found that the climatic regions of precipitation could be classified by means of the interstational analysis for the correlations. Corrleation coefficients in interstational relationship of precipitation are lowest in autumn which characterizeds a strong locality while the highest value shows a relatively weak locality in winter. Interseasonal relationship between summer and winter precipitation shows mostly 10 percent significant level with all positive values. The magnitude of the variation coefficients are appeared to be in the order of winter, autumn, spring and summer. It is shown that the highest which is winter ranges between 0.33 0.58, and for the lowest summer, 0.26-0.44, respectively in the areal distribution of the coefficient. The secular changes of the variation coefficient in the recent trend show increases in spring at two station; Seoul and Incheon, in summer at Busan and in autumn at two stations; Busan and Incheon while in winter show devreases at the whole stations. An annual variation seems to show generally a constant trend as whole for all the stations.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2015년도 학술발표회
• /
• pp.226-226
• /
• 2015

The complex climate system regarding human actions is well represented through global climate models (GCMs). The output from GCMs provides useful information about the rate and magnitude of future climate change. Especially, the temperature variable is most reliable among other GCM outputs. However, hydrological variables (e.g. precipitation) from GCM outputs for future climate change contain too high uncertainty to use in practice. Therefore, we propose a method that simulates temperature variable with increasing in a certain level (e.g. 0.5oC or 1.0oC increase) as a global warming scenario from observed data. In addition, a hydrometeorological variable can be simulated employing block-wise sampling technique associated with the temperature simulation. The proposed method was tested for assessing the future change of the seasonal precipitation in South Korea under global warming scenario. The results illustrate that the proposed method is a good alternative to levy the variation of hydrological variables under global warming condition.

• 대기
• /
• 제32권2호
• /
• pp.135-148
• /
• 2022

This study investigates the influence of atmospheric river (AR) on precipitation over South Korea with a focus on regional characteristics. The 42-year-long catalog of ARs, which is obtained by applying the automatic AR detection algorithm to ERA5 reanalysis data and the insitu precipitation data recorded at 56 weather stations across the country are used to quantify their relationship. Approximately 51% of the climatological annual precipitation is associated with AR. The AR-related precipitation is most pronounced in summer by approximately 58%, while only limited fraction of precipitation (26%) is AR-related in winter. The heavy precipitation (> 30 mm day^-1) is more prone to AR activity (59%) than weak precipitation (5~30 mm day^-1; 33%) in all seasons. By grouping weather stations into the four sub-regions based on orography, it is found that the contribution of AR precipitation to the total is largest in the southern coast (57%) and smallest in the eastern coast (36%). Similar regional variations in AR precipitation fractions also occur in weak precipitation events. The regional contrast between the northern and southern stations is related to the seasonal variation of AR-frequency. In addition, the regional contrast between the western and eastern stations is partly modulated by the orographic forcing. The fractional contribution of AR to heavy precipitation exceeds 50% in all seasons, but this is true only in summer along the eastern coast. This result indicates that ARs play a critical role in heavy precipitation in South Korea, thus routine monitoring of ARs is needed for improving operational hydrometeorological forecasting.

• The Plant Pathology Journal
• /
• 제36권5호
• /
• pp.406-417
• /
• 2020

Early warning services for crop diseases are valuable when they provide timely forecasts that farmers can utilize to inform their disease management decisions. In South Korea, collaborative disease controls that utilize unmanned aerial vehicles are commonly performed for most rice paddies. However, such controls could benefit from seasonal disease early warnings with a lead time of a few months. As a first step to establish a seasonal disease early warning service using seasonal climate forecasts, we developed the EPIRICE Daily Risk Model for rice blast by extracting and modifying the core infection algorithms of the EPIRICE model. The daily risk scores generated by the EPIRICE Daily Risk Model were successfully converted into a realistic and measurable disease value through statistical analyses with 13 rice blast incidence datasets, and subsequently validated using the data from another rice blast experiment conducted in Icheon, South Korea, from 1974 to 2000. The sensitivity of the model to air temperature, relative humidity, and precipitation input variables was examined, and the relative humidity resulted in the most sensitive response from the model. Overall, our results indicate that the EPIRICE Daily Risk Model can be used to produce potential disease risk predictions for the seasonal disease early warning service.

• 한국환경생태학회지
• /
• 제34권1호
• /
• pp.55-62
• /
• 2020

이 연구는 강원대학교 학술림 내의 산지계류를 대상으로 2년간(2017~2018)의 현지 모니터링에 기초하여 수온과 강우, 유량 및 기온 등 환경인자간의 관계를 분석하고, 계절별 산지계류의 수온변화 예측기법에 대하여 검토하였다. 동절기를 제외한 봄, 여름 및 가을철로 구분하여 단계적 다중선형회귀분석을 실시하였으며, 계절별 산지계류의 수온변화에 미치는 환경인자의 영향을 분석하였다. 그 결과, 산지계류의 일평균 수온은 봄철 6.9~17.7℃로 기온과 유의적 관계를 나타내었고, 여름철 12.2~26.3℃로 기온, 유량과 유의적 관계를 나타냈으며, 가을철 3.6~19.3℃로 기온 및 유량과 유의적 관계를 나타내는 등 계절별로 산지계류의 수온에 미치는 영향인자는 다르게 나타났다. 다중선형회귀식은 봄철 (0.553×기온)+(0.086×유량)+4.145(R²=0.505; p<0.01), 여름철 (0.756×기온)+(-0.072×유량)+2.670(R²=0.510; p<0.01), 가을철 (0.738×기온)+(0.028×강우)+2.660(R²=0.844; p<0.01)이었다. 도출된 모든 회귀식의 결정계수(R²)는 기온만으로 예측한 경우보다 높게 나타났고, 봄철에서 가을철로 갈수록 증가하였다. 향후 정밀도 높은 산지계류의 수온변화 예측을 위해서는 지속적인 현지 모니터링과 함께 시·공간적 데이터의 확보가 중요하다고 판단된다.

• 한국대기환경학회지
• /
• 제13권5호
• /
• pp.371-381
• /
• 1997

Precipitation sampls were collected in Chonju-city during October 1994 to September 1995 and were analysed for major ions (N $a^{+}$, $K^{+}$, $Ca^{2+}$, $Mg^{2+}$, C $l^{[-10]}$ , NO/$_3$, S $O_4$$^{2-}$) and trace metals (Al, Cd, Ni, Pb, Sr, Zn) in addition to pH, in order to understand the chemical characteristics of acid rain and to estimate the origin of the determined ions. Most rain showed a neutral or alkaline character, and only 35% had a pH lower than 5.6. S $O_4$$^{2-}$ and N $O_3$$^{[-10]}$ are identified as the primary contributors to precipitation acidity in this region. Neutralization of precipitation acidity occurs as a result of the dissolution of alkaline compounds containing $Ca^{2+}$, $Mg^{2+}$ and $K^{+}$. S $O_4$$^{2-}$ and N $O_3$$^{[-10]}$ precipitation concentrations exhibit a seasonal pattern in which higher concentrations are observed during spring months and lower concentrations during summer months. However, the seasonal behavior of $H^{+}$ concentrations differs from this pattern, in that the highest concentrations occur during autumn months, owing to the different influence of neutralization processes. In all rain, S $O_4$$^{2-}$ concentration exceeded NO/$_3$$^{[-10]}$ concentration. The contribution of maritime sources to the total S $O_4$$^{2-}$ concentration was very low or negligible. For rain strongly affacted by yellow sand, $Ca^{2+}$, $Mg^{2+}$ and $K^{+}$ ions show a sharp increase in concentration, reflecting the increased amount of dust and soil suspended in atmosphere. At the same time, S $O_4$$^{2-}$ and N $O_3$$^{[-10]}$ concentrations are at their highest levels while $H^{+}$ values are not comparably elevated, presumably beacause much of the acidity has been neutralized by alkaline substances. The seasonal variance of trace metal concentrations in rainwater is similar to that of major cations. The annual wet flux of acidic pollutants and trace metals wat calculated to be as follows: N $O_3$$^{[-10]}$ ; 2.32 g/$m^2$, S $O_4$$^{2-}$, 5.34 g/$m^2$, Al; 6.30 mg/$m^2$, Cd; 0.62 mg/$m^2$, Ni; 4.08 mg/$m^2$, Pb: 9.76 mg/$m^2$, Sr; 5.94 mg/$m^2$, Zn; 111 mg/$m^2$./$m^2$.

• 한국지구과학회지
• /
• 제35권1호
• /
• pp.88-94
• /
• 2014

현재 최고 수준의 대순환 모형에서 북동아시아 여름몬순 강도의 계절예측 능력은 낮으나 북서태평양 아열대 고기압 강도의 예측률은 상대적으로 높다. 북서태평양 아열대 고기압은 북서태평양 지역 및 동아시아 지역에서 가장 주된 기후 변동성이다. 본 연구에서 NCEP 계절예측시스템에서 예측된 북서태평양 아열대 고기압의 예측성에 대해 논의될 것이다. 한편, 북동아시아 여름몬순의 경년변동성은 북서태평양 아열대 고기압과 높은 상관성을 가지고 있다. 본 연구에서는 이 관계에 근거하여, NCEP 계절예측시스템과 정준상관분석을 이용한 계절예측 모형을 제안하고 그 예측률을 평가하였다. 이 방법은 북동아시아 지역 여름철 강수량 편차에 대한 계절예측에 있어 통계적으로 유의한 예측성능을 제공한다.

• 대기
• /
• 제26권1호
• /
• pp.59-72
• /
• 2016

The comparison of prediction errors in geopotential height, temperature, and precipitation forecasts is made quantitatively to evaluate medium-range forecast skills between Global Seasonal Forecasting System version 5 (GloSea5) and Unified Model (UM) in operation by Korea Meteorological Administration during 2014. In addition, the performances in prediction of sea surface temperature anomaly in NINO3.4 region, Madden and Julian Oscillation (MJO) index, and tropical storms in western north Pacific are evaluated. The result of evaluations appears that the forecast skill of UM with lower values of root-mean square error is generally superior to GloSea5 during forecast periods (0 to 12 days). The forecast error tends to increase rapidly in GloSea5 during the first half of the forecast period, and then it shows down so that the skill difference between UM and GloSea5 becomes negligible as the forecast time increases. Precipitation forecast of GloSea5 is not as bad as expected and the skill is comparable to that of UM during 10-day forecasts. Especially, in predictions of sea surface temperature in NINO3.4 region, MJO index, and tropical storms in western Pacific, GloSea5 shows similar or better performance than UM. Throughout comparison of forecast skills for main meteorological elements and weather extremes during medium-range, the effects of initial and model errors in atmosphere-ocean coupled model are verified and it is suggested that GloSea5 is useful system for not only seasonal forecasts but also short- and medium-range forecasts.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2022년도 학술발표회
• /
• pp.141-141
• /
• 2022

Drought is a global phenomenon that affects almost all landscapes and causes major damages. Due to non-linear nature of contributing factors, drought occurrence and its severity is characterized as stochastic in nature. Early warning of impending drought can aid in the development of drought mitigation strategies and measures. Thus, drought forecasting is crucial in the planning and management of water resource systems. The primary objective of this study is to make improvement is existing drought forecasting techniques. Therefore, we proposed an improved version of Seasonal Autoregressive Integrated Moving Average (SARIMA) model (MD-SARIMA) for reliable drought forecasting with three years lead time. In this study, we selected four watersheds of Han River basin in South Korea to validate the performance of MD-SARIMA model. The meteorological data from 8 rain gauge stations were collected for the period 1973-2016 and converted into watershed scale using Thiessen's polygon method. The Standardized Precipitation Index (SPI) was employed to represent the meteorological drought at seasonal (3-month) time scale. The performance of MD-SARIMA model was compared with existing models such as Seasonal Naive Bayes (SNB) model, Exponential Smoothing (ES) model, Trigonometric seasonality, Box-Cox transformation, ARMA errors, Trend and Seasonal components (TBATS) model, and SARIMA model. The results showed that all the models were able to forecast drought, but the performance of MD-SARIMA was robust then other statistical models with Wilmott Index (WI) = 0.86, Mean Absolute Error (MAE) = 0.66, and Root mean square error (RMSE) = 0.80 for 36 months lead time forecast. The outcomes of this study indicated that the MD-SARIMA model can be utilized for drought forecasting.