• Journal of Wetlands Research
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• v.15 no.3
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• pp.339-346
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• 2013

This study analyzes the application possibilities of the satellite-derived precipitation to water resources field. Precipitation observed by ground gauges and climate prediction center morphing method (CMORPH) which is global scale precipitation estimated by National Oceanic and Atmospheric Administration Climate Prediction Center (NOAA CPC) using satellite images are compared to evaluate the quality of precipitation estimated from satellite images. Precipitation data from 10-years (2002 to 2011) is applied. The correlation coefficient of 1-day cumulative precipitation is 0.87, but the 1-year precipitation is 4 to 5 times different. The variability of root mean square error (RMSE) become smaller as temporal resolution lower. On the results for the watershed scale, the precipitation from gauges and CMORPH shows better agreement as the watershed become larger.

• Journal of the Korean earth science society
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• v.44 no.3
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• pp.185-195
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• 2023

The prolonged and heavy East Asian summer precipitation in 2020 may have been caused by an enhanced Madden-Julian Oscillation (MJO), which requires evaluation using forecast models. We examined the performance of GloSea6, an operational forecast model, in predicting the East Asian summer precipitation during July 2020, and investigated the role of MJO in the extreme rainfall event. Two experiments, CON and EXP, were conducted using different convection schemes, 6A and 5A, respectively to simulate various aspects of MJO. The EXP runs yielded stronger forecasts of East Asian precipitation for July 2020 than the CON runs, probably due to the prominent MJO realization in the former experiment. The stronger MJO created stronger moist southerly winds associated with the western North Pacific subtropical high, which led to increased precipitation. The strengthening of the MJO was found to improve the prediction accuracy of East Asian summer precipitation. However, it is important to note that this study does not discuss the impact of changes in the convection scheme on the modulation of MJO. Further research is needed to understand other factors that could strengthen the MJO and improve the forecast.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.330-330
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• 2022

우리나라에서 발생하는 기상 재해 현상은 주로 태풍, 집중호우, 장마 등 인명 및 경제적인 피해가 크며, 단기간에 국지적으로 나타난다. 현재 재해 감시 및 예보는 주로 종관기상관측체계를 이용하고 있다. 하지만, 우리나라의 복잡한 지형, 인구 밀집 지형, 관측 시기가 일정하지 않은 지형과 같은 조건에서 미계측 자료 및 지역이 다수 존재 때문에 강수의 공간 분포와 강도에 대한 정밀한 정보를 제공하지 못하는 실정이다. 최근 광범위한 관측영역과 공간 분해능의 개선, 자료추출 알고리즘의 개발로 전세계적으로 위성영상 기반 기상관측 자료의 활용성이 증대되고 있다. 본 연구에서는 한반도 지역의 지상 관측데이터와 전지구 격자형 위성 강우자료를 비교하여 한반도의 적용성을 분석하고자 한다. 다양한 위성영상 기반 기상자료인 Climate Hazards Groups InfraRed Precipitation with Station (CHIRPS), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), Global Precipitation Climatology Centre (GPCC), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) 4개의 강우위성영상을 수집하여, 1991년부터 2020년까지 30년 데이터를 활용하였다. 강수량 변동성 비교를 위하여 기상청의 종관기상관측장비 (Automated Synoptic Observation System, ASOS), 자동기상관측시설 (Automatic Weather System, AWS) 데이터와 상관 분석을 수행하고, 강우위성영상의 국내 적합성을 판단하고자 한다.

• Communications for Statistical Applications and Methods
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• v.16 no.5
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• pp.851-858
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• 2009

In the last decades, there has been much interest in climate variability because its change has dramatic effects on humanity. Especially, the precipitation data are measured over space and their spatial association is so complicated. So we should take into account such a spatial dependency structure while analyzing the data. However, in linear models for analyzing the data, data sets show severely skewed distribution. In the paper, we consider the Box-Cox transformation to satisfy the normal distribution prior to the analysis, and employ a Bayesian hierarchical framework to investigate the spatial patterns. The data set we considered is monthly average precipitation of the third quarter of 2007 obtained from 347 automated monitoring stations in Contiguous South Korea.

• Atmosphere
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• v.18 no.2
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• pp.83-95
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• 2008

In this study we have investigated the preceding eighteen large-scale climate indices with a lead time from zero to twelve months that have an influence on the variability of temperature and precipitation in Korea in order to understand which climate indices are overall available as predictors for long-range forecasting. We also have studied the dynamic link between preceding large-scale climate indices and regional climate using singular value decomposition analysis (SVDA) and correlation analysis (CA). Based on the coupled mode between large-scale circulation and regional climate, and correlation pattern between the preceding large-scale climate indices and large-scale circulation, the level of significance on climate indices as a predictor for monthly mean temperature and precipitation was evaluated for 5 and 1% level.

• Atmosphere
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• v.28 no.1
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• pp.85-97
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• 2018

This study evaluates the performance of the Weather Research and Forecasting (WRF) model in reproducing the present-day (1981~2005) precipitation over Far East Asia and South Korea. The WRF model is configured with 25-km horizontal resolution within the context of the COordinated Regional climate Downscaling Experiment (CORDEX) - East Asia Phase 2. The initial and lateral boundary forcing for the WRF simulation are derived from European Centre for Medium-Range Weather Forecast Interim reanalysis. According to our results, WRF model shows a reasonable performance to reproduce the features of precipitation, such as seasonal climatology, annual and inter-annual variabilities, seasonal march of monsoon rainfall and extreme precipitation. In spite of such model's ability to simulate major features of precipitation, systematic biases are found in the downscaled simulation in some sub-regions and seasons. In particular, the WRF model systematically tends to overestimate (underestimate) precipitation over Far East Asia (South Korea), and relatively large biases are evident during the summer season. In terms of inter-annual variability, WRF shows an overall smaller (larger) standard deviation in the Far East Asia (South Korea) compared to observation. In addition, WRF overestimates the frequency and amount of weak precipitation, but underestimates those of heavy precipitation. Also, the number of wet days, the precipitation intensity above the 95 percentile, and consecutive wet days (consecutive dry days) are overestimated (underestimated) over eastern (western) part of South Korea. The results of this study can be used as reference data when providing information about projections of fine-scale climate change over East Asia.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3B
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• pp.295-303
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• 2010

The variability of vegetation is strongly related to the variability of hydrometeorological factors such as precipitation, temperature, runoff and so on. Analysis of the variability of vegetation will aid to understand the regional impact of climate change. Thus we analyzed the spatial-temporal variability of NOAA(National Oceanic and Atmospheric Administration)/AVHRR(Advanced Very High Resolution Radiometer) NDVI(Normalized Difference Vegetation Index). In the results from Mann-Kendall test, there is no significant linear trend of annual NDVI from 1982 to 2006 in the most area except the downward trend on the significance level 90% in the Guem-river basin area. In addition, using EOF(Empirical Orthogonal Function) analysis, the variability of NDVI in the region of higher latitude and altitude is higher than that in the other region since the spatial variability of NDVI follows the latitudinal gradient. Also we could get higher NDVI in June, July, August and September. We had the highest NDVI in Han-river basin area and the lowest in Je-Ju island.

• Journal of the Korean earth science society
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• v.35 no.1
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• pp.88-94
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• 2014

The seasonal predictability of the intensity of the Northeast Asian summer monsoon is low while that of the western North subtropical high variability is, when state-of-the-art general circulation models are used, relatively high. The western North Pacific subtropical high dominates the climate anomalies in the western North Pacific-East Asian region. This study discusses the predictability of the western North Pacific subtropical High variability in the National Centers for Environmental Prediction Climate Forecast System (NCEP CFS). The interannual variability of the Northeast Asian summer monsoon is highly correlated with one of the western North Pacific subtropical Highs. Based on this relationship, we suggest a seasonal prediction model using NCEP CFS and canonical correlation analysis for Northeast Asian summer precipitation anomalies and assess the predictability of the prediction model. This methodology provides significant skill in the seasonal prediction of the Northeast Asian summer rainfall anomalies.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.46 no.6
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• pp.868-877
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• 2013

To understand the effects of marine environmental and meteorological parameters on laver Porphyra yezoensis production at Nakdong River Estuary, we analyzed marine environmental (water temperature, salinity, nutrients, etc.) and meteorological properties (air temperature, wind speed, precipitation, sunshine hours) with yearly and monthly variations in laver production over 10 years (2003-2013). Air and water temperature, wind speed, sunshine hours and precipitation were major factors affecting yearly variability in laver production at the Nakdong River Estuary. Lower air and water temperatures together with higher levels of nutrients and sunshine and stronger wind speeds resulted in higher laver harvests. Salinity and nitrogen did not show clear correlations with laver production, mainly due to the plentiful supply of nitrogen from river discharge and the low frequency of environmental measurements, which resulted in low statistical confidence. However, environmental factors affecting monthly laver production were related to the life cycle (culturing stage) of Porphyra yezoensis and were somewhat different from factors affecting annual laver production. In November, a young laver needs lower water temperatures for rapid growth, while a mature laver needs much stronger winds and more sunshine, as well as lower temperatures for massive production and effective photosynthesis, mostly in December and January. However, in spring (March), more stable environments with fewer fluctuations in air temperature are needed to sustain the production of newly deployed culture-nets ($2^{nd}$ time culture). These results indicate that rapid changes in weather and marine environments caused by global climate change will negatively affect laver production and, thus, to sustain the yield of and predict future variability in laver production at the Nakdong River estuary, environmental variation around laver culturing farms needs to be monitored with high resolution in space and time.

• Journal of the Korean Geographical Society
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• v.48 no.2
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• pp.184-203
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• 2013

This study analyzes the variability of Korean summer rainfall associated with the tropical low-frequency oscillation using long-term observation data. From the EOF analysis, the first mode showed opposite phase between the South and the North Korea with the regime shift in rainfall variability since the mid-1990s. The summer precipitation over South Korea tends to increase in southern part during strong El Ni$\tilde{n}$o where the warm sea surface temperature extends to far eastern tropical Pacific. In weak La Ni$\tilde{n}$a, the increased precipitation directly influences from the western tropical Pacific to the mid-latitude. In June, the rainfall over South Korea is positively correlated with the Indian Summer Monsoon while in July, it is negatively correlated with the Western North Pacific Summer Monsoon. In August, highly negative correlation between the rainfall over South Korea and the Indian Summer Monsoon is found.