• Title/Summary/Keyword: precipitation region

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Classification of the Core Climatic Region Established by the Entropy of Climate Elements - Focused on the Middle Part Region - (기후요소의 엔트로피에 의한 핵심 기후지역의 구분 - 중부지방을 중심으로 -)

  • Park, Hyun-Wook;Chung, Sung-Suk;Park, Keon-Yeong
    • Journal of the Korean earth science society
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    • v.27 no.2
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    • pp.159-176
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    • 2006
  • Geographic factors and mathmatical location of the Korean Peninsula have great influences on the variation patterns and appearances over a period of ten days of summer precipitation. In order to clarify the influence of several climate factors on precise climate classification in the middle part region of the Korea, weather entropy and the information ratio were calculated on the basis of information theory and of the data of 25 site observations. The data used for this study are the daily precipitation phenomenon over a period of ten days of summer during the recent thirteen years (1991-2003) at the 25 stations in the middle part region of the Korea. It is divided into four classes of no rain, $0.1{\sim}10.0mm/day,\;10.1{\sim}30.0mm/day$, 30.1mm over/day. Their temporal and spatial change were also analyzed. The results are as follows: the maximum and minimum value of calculated weather entropy are 1.870 bits at Chuncheon in the latter ten days of July and 0.960 bits at Ganghwa during mid September, respectively. And weather entropy in each observation sites tends to be larger in the beginning of August and smaller towards the end of September. The largest and smallest values of weather representative ness based on information ratio were observed at Chungju in the beginning of June and at Deagwallyeong towards the end of July. However, the largest values of weather representativeness came out during the middle or later part of September when 15 sites were adopted as the center of weather forecasting. The representative core region of weather forecasting and climate classification in the middle part region of the Korea are inside of the triangle region of the Buyeo, Incheon, and Gangneung.

Vertical Atmospheric Structure and Sensitivity Experiments of Precipitation Events Using Winter Intensive Observation Data in 2012 (2012년 겨울철 특별관측자료를 이용한 강수현상 시 대기 연직구조와 민감도 실험)

  • Lee, Sang-Min;Sim, Jae-Kwan;Hwang, Yoon-Jeong;Kim, Yeon-Hee;Ha, Jong-Chul;Lee, Yong-Hee;Chung, Kwan-Young
    • Atmosphere
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    • v.23 no.2
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    • pp.187-204
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    • 2013
  • This study analyzed the synoptic distribution and vertical structure about four cases of precipitation occurrences using NCEP/NCAR reanalysis data and upper level data of winter intensive observation to be performed by National Institute of Meteorological Research at Bukgangneung, Incheon, Boseong during 63days from 4 JAN to 6 MAR in 2012, and Observing System Experiment (OSE) using 3DVAR-WRF system was conducted to examine the precipitation predictability of upper level data at western and southern coastal regions. The synoptic characteristics of selected precipitation occurrences were investigated as causes for 1) rainfall events with effect of moisture convergence owing to low pressure passing through south sea on 19 JAN, 2) snowfall events due to moisture inflowing from yellow sea with propagation of Siberian high pressure after low pressure passage over middle northern region on 31 JAN, 3) rainfall event with effect of weak pressure trough in west low and east high pressure system on 25 FEB, 4) rainfall event due to moisture inflow according to low pressures over Bohai bay and south eastern sea on 5 MAR. However, it is identified that vertical structure of atmosphere had different characteristics with heavy rainfall system in summer. Firstly, depth of convection was narrow due to absence of moisture convergence and strong ascending air current in middle layer. Secondly, warm air advection by veering wind with height only existed in low layer. Thirdly, unstable layer was limited in the narrow depth due to low surface temperature although it formed, and also values of instability indices were not high. Fourthly, total water vapor amounts containing into atmosphere was small due to low temperature distribution so that precipitable water vapor could be little amounts. As result of OSE conducting with upper level data of Incheon and Boseong station, 12 hours accumulated precipitation distributions of control experiment and experiments with additional upper level data were similar with ones of observation data at 610 stations. Although Equitable Threat Scores (ETS) were different according to cases and thresholds, it was verified positive influence of upper level data for precipitation predictability as resulting with high improvement rates of 33.3% in experiment with upper level data of Incheon (INC_EXP), 85.7% in experiment with upper level data of Boseong (BOS_EXP), and 142.9% in experiment with upper level data of both Incheon and Boseong (INC_BOS_EXP) about accumulated precipitation more than 5 mm / 12 hours on 31 January 2012.

Downscaling GPM Precipitation Using Finer-scale MODIS Based Optical Image in Korean Peninsula (MODIS 광학 영상 자료를 통한 한반도 GPM 강우 자료의 상세화 기법)

  • Oh, Seungcheol;Jeong, Jaehwan;Lee, Seulchan;Choi, Minha
    • Korean Journal of Remote Sensing
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    • v.36 no.5_1
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    • pp.749-762
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    • 2020
  • Precipitation is closely related to various hydrometeorological phenomena, such as runoff and evapotranspiration. In Korean Peninsula, observing rainfall intensity using weather radar and rain gauge network is dominating due to their accurate, intuitive and precise detecting power. However,since these methods are not suitable at ungauged regions, rainfall detection using satellite is required. Satellite-based rainfall data has coarse spatial resolution (10 km, 25 km), and has a limited range of usage due to its reliability of data. The aim of this study is to obtain finer scale precipitation. Especially, to make the applicability of satellite higher at ungauged regions, 10 km satellite-based rainfall data was downscaled to 1 km data using MODerate Resolution Imaging Spectroradiometer (MODIS) based cloud property. Downscaled precipitation was verified in urban region, which has complex topographical and environmental characteristics. Correlation coefficient was similar in summer (+0), decreased in spring (-0.08) and autumn (-0.01), and increased in winter (+0.04) season compared to Global Precipitation Measurement (GPM) based precipitation. Downscaling without calibration using in situ data could be useful in areas where rain gauge system is not sufficient or ground observations are rarely available.

Performance of NCAR Regional Climate Model in the Simulation of Indian Summer Monsoon (NCAR 지역기후모형의 인도 여름 몬순의 모사 성능)

  • Singh, Gyan Prakash;Oh, Jai-Ho
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.12 no.3
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    • pp.183-196
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    • 2010
  • Increasing human activity due to rapid economic growth and land use change alters the patterns of the Asian monsoon, which is key to crop yields in Asia. In this study, we tested the performance of regional climate model (RegCM3) by simulating important components of Indian summer monsoon, including land-ocean contrast, low level jet (LLJ), Tibetan high and upper level Easterly Jet. Three contrasting rain years (1994: excess year, 2001: normal year, 2002: deficient year) were selected and RegCM3 was integrated at 60 km horizontal resolution from April 1 to October 1 each year. The simulated fields of circulations and precipitation were validated against the observation from the NCEP/NCAR reanalysis products and Global Precipitation Climatology Centre (GPCC), respectively. The important results of RegCM3 simulations are (a) LLJ was slightly stronger and split into two branches during excess rain year over the Arabian Sea while there was no splitting during normal and deficient rain years, (b) huge anticyclone with single cell was noted during excess rain year while weak and broken into two cells in deficient rain year, (c) the simulated spatial distribution of precipitation was comparable to the corresponding observed precipitation of GPCC over large parts of India, and (d) the sensitivity experiment using NIMBUS-7 SMMR snow data indicated that precipitation was reduced mainly over the northeast and south Peninsular India with the introduction of 0.1 m of snow over the Tibetan region in April.

Combining Bias-correction on Regional Climate Simulations and ENSO Signal for Water Management: Case Study for Tampa Bay, Florida, U.S. (ENSO 패턴에 대한 MM5 강수 모의 결과의 유역단위 성능 평가: 플로리다 템파 지역을 중심으로)

  • Hwang, Syewoon;Hernandez, Jose
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.14 no.4
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    • pp.143-154
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    • 2012
  • As demand of water resources and attentions to changes in climate (e.g., due to ENSO) increase, long/short term prediction of precipitation is getting necessary in water planning. This research evaluated the ability of MM5 to predict precipitation in the Tampa Bay region over 23 year period from 1986 to 2008. Additionally MM5 results were statistically bias-corrected using observation data at 33 stations over the study area using CDF-mapping approach and evaluated comparing to raw results for each ENSO phase (i.e., El Ni$\tilde{n}$o and La Ni$\tilde{n}$a). The bias-corrected model results accurately reproduced the monthly mean point precipitation values. Areal average daily/monthly precipitation predictions estimated using block-kriging algorithm showed fairly high accuracy with mean error of daily precipitation, 0.8 mm and mean error of monthly precipitation, 7.1 mm. The results evaluated according to ENSO phase showed that the accuracy in model output varies with the seasons and ENSO phases. Reasons for low predictions skills and alternatives for simulation improvement are discussed. A comprehensive evaluation including sensitivity to physics schemes, boundary conditions reanalysis products and updating land use maps is suggested to enhance model performance. We believe that the outcome of this research guides to a better implementation of regional climate modeling tools in water management at regional/seasonal scale.

Observation-based Analysis of Climate Change using Meteorological Data of Gangneung (기상 관측 자료를 이용한 강릉의 기후변화 추세 분석)

  • Lee, Jaeho;Baek, Hee-Jeong;Hyun, Yu-Kyung;Cho, Chunho
    • Journal of Climate Change Research
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    • v.2 no.2
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    • pp.133-141
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    • 2011
  • This study is to identify the trend of climate change in Gangwon-do by examining accumulated climate data such as temperature and precipitation in Gangneung city over the past about 100 years. The annual mean temperature and precipitation in Gangneung have increased by $1.4^{\circ}C$ and 14.7%, respectively, over the last 98 years (1912~2009). The trends of Gangneung showed that precipitation has intensified as the number of precipitation days decreased while its amount increased during the period. Based on the temperature data, spring and summer began earlier whereas the onsets of fall and winter were delayed. Summer has become longer and winter shorter by about a month. Averaging observation data from seven weather stations in Gangwon-do, the annual mean temperature and precipitation have increased by $0.8^{\circ}C$ and 21.0% respectively over the last 37 years (1973~2009). By region, Wonju city recorded the biggest increase of $1.6^{\circ}C$ in the annual mean temperature while Sokcho city the smallest increase of $0.4^{\circ}C$. In the annual mean precipitation, Daegwallweong recorded the biggest change of 22.2% and Wonju city the smallest of 12.0%.

A Study on Forecast Accuracies by the Localized Land Forecast Areas over South Korea (육상 국지 예보 구역의 예보 정확도에 관한 연구)

  • Park, Chang-Yong;Choi, Young-Eun;Kim, Seung-Bae
    • Journal of the Korean Geographical Society
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    • v.42 no.1 s.118
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    • pp.1-14
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    • 2007
  • This study aimed to evaluate weather forecast accuracies of minimum temperature, maximum temperature, precipitation and sky cover by the localized land forecast areas over South Korea Average forecast accuracy score of precipitation was the lowest while that of sky cover was the highest during the study period Overall forecast accuracy scores for Gangwon-do was the lowest while those for Gyeongsangnam-do and Gyeongsangbuk-do were higher than other areas. The frequencies of perfect forecast(eight points) by seasons, were the highest during winter and the lowest during summer. pressure pattern analyses for days when forecast accuracy scores were poor, showed that precipitation forecast accuracy scores were lower due to the movement of the stationary fronts during summers. When continental polar air masses expanded, forecast accuracy of temperature became greatly lower during autumns and winters As the migratory anticyclone pattern rapidly moved, forecast accuracy became lower during springs and autumns. Forecast accuracies were compared by wind directions at 850hPa for the Young-dong region where forecast accuracy was the lowest. Forecast accuracy scores on minimum and maximum temperatures were low when winds were westerlies and forecast accuracy scores of precipitation were low when winds were easterlies.

Evaluation of Reservoir Drought Response Capability Considering Precipitation of Non-irrigation Period using RCP Scenario (RCP 시나리오에 따른 비관개기 누적강수량을 고려한 둑높이기 저수지의 미래 가뭄대응능력 평가)

  • Bang, JeHong;Lee, Sang-Hyun;Choi, Jin-Yong;Lee, Sung-Hack
    • Journal of The Korean Society of Agricultural Engineers
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    • v.59 no.1
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    • pp.31-43
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    • 2017
  • Recent studies about irrigation water use have focused on agricultural reservoir operation in irrigation period. At the same time, it is significant to store water resource in reservoir during non-irrigation period in order to secure sufficient water in early growing season. In this study, Representative Concentration Pathways (RCP) 4.5, 8.5 scenarios with the Global Climate Model (GCM) of The Second Generation Earth System Model (CanESM2) were downscaled with bias correlation method. Cumulative precipitation during non-irrigation season, October to March, was analyzed. Interaction between cumulative precipitation and carry-over storage was analyzed with linear regression model for ten study reservoirs. Using the regression model, reservoir drought response ability was evaluated with expression of excess and deficiency. The results showed that future droughts will be more severe than past droughts. Especially in case of non-exceedance probability of 10%, drought in southern region seemed to be serious. Nine study reservoirs showed deficiency range from 10% to 55%, which turned out to be vulnerable for future drought. Only Jang-Chan reservoir was secure for early growing season in spite of drought with deficiency of 8% and -2%. The results of this study represents current agricultural reservoirs have vulnerability for the upcoming drought.

Evaluation of Performance and Uncertainty for Multi-RCM over CORDEX-East Asia Phase 2 region (CORDEX-동아시아 2단계 영역에 대한 다중 RCM의 모의성능 및 불확실성 평가)

  • Kim, Jin-Uk;Kim, Tae-Jun;Kim, Do-Hyun;Kim, Jin-Won;Cha, Dong-Hyun;Min, Seung-Ki;Kim, Yeon-Hee
    • Atmosphere
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    • v.30 no.4
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    • pp.361-376
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    • 2020
  • This study evaluates multiple Regional Climate Models (RCMs) in simulating temperature and precipitation over the Far East Asia (FEA) and estimates the portions of the total uncertainty originating in the RCMs and the driving Global Climate Models (GCMs) using nine present-day (1981~2000) climate data obtained from combinations of three GCMs and three RCMs in the CORDEX-EA phase2. Downscaling using the RCMs generally improves the present temperature and precipitation simulated in the GCMs. The mean temperature climate in the RCM simulations is similar to that in the GCMs; however, RCMs yield notably better spatial variability than the GCMs. In particular, the RCMs generally yield positive added values to the variability of the summer temperature and the winter precipitation. Evaluating the uncertainties by the GCMs (VARGCM) and the RCMs (VARRCM) on the basis of two-way ANOVA shows that VARRCM is greater than VARGCM in contrast to previous studies which showed VARGCM is larger. In particular, in the winter temperature, the ocean has a very large VARRCM of up to 30%. Precipitation shows that VARRCM is greater than VARGCM in all seasons, but the difference is insignificant. In the following study, we will analyze how the uncertainty of the climate model in the present-day period affects future climate change prospects.

How do diverse precipitation datasets perform in daily precipitation estimations over Africa?

  • Brian Odhiambo Ayugi;Eun-Sung Chung
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.158-158
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    • 2023
  • Characterizing the performance of precipitation (hereafter PRE) products in estimating the uncertainties in daily PRE in the era of global warming is of great value to the ecosystem's sustainability and human survival. This study intercompares the performance of different PRE products (gauge-based, satellite and reanalysis) sourced from the Frequent Rainfall Observations on GridS (FROGS) database over diverse climate zones in Africa and identifies regions where they depict minimal uncertainties in order to build optimal maps as a guide for different climate users. This is achieved by utilizing various techniques, including the triple collection (TC) approach, to assess the capabilities and limitations of different PRE products over nine climatic zones over the continent. For daily scale analysis, the uncertainties in light PRE (0.1 5mm/day) are prevalent over most regions in Africa during the study duration (2001-2016). Estimating the occurrence of extreme PRE events based on daily PRE 90th percentile suggests that extreme PRE is mainly detected over central Africa (CAF) region and some coastal regions of west Africa (WAF) where the majority of uncorrected satellite products show good agreement. The detection of PRE days and non-PRE days based on categorical statistics suggests that a perfect POD/FAR score is unattainable irrespective of the product type. Daily PRE uncertainties determined based on quantitative metrics show that consistent, satisfactory performance is demonstrated by the IMERG products (uncorrected), ARCv2, CHIRPSv2, 3B42v7.0 and PERSIANN_CDRv1r1 (corrected), and GPCC, CPC_v1.0, and REGEN_ALL (gauge) during the study period. The optimal maps that show the classification of products in regions where they depict reliable performance can be recommended for various usage for different stakeholders.

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