• Title/Summary/Keyword: Climatological study

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Database Construction of High-resolution Daily Meteorological and Climatological Data Using NCAM-LAMP: Sunshine Hour Data (NCAM-LAMP를 이용한 고해상도 일단위 기상기후 DB 구축: 일조시간 자료를 중심으로)

  • Lee, Su-Jung;Lee, Seung-Jae;Koo, Ja-seob
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.22 no.3
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    • pp.135-143
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    • 2020
  • Shortwave radiation and sunshine hours (SHOUR) are important variables having many applications, including crop growth. However, observational data for these variables have low horizontal resolution, rendering its application to related research and decision making on f arming practices challenging. In the present study, hourly solar radiation data were physically generated using the Land-Atmosphere Modeling Package (LAMP) at the National Center f or Agro-Meteorology, and then daily SHOUR fields were calculated through statistical downscaling. After data quality evaluation, including case studies, the SHOUR data were added to the existing publically accessible LAMP daily database. The LAMP daily dataset, newly updated with SHOUR, has been provided operationally as input data to the "Gyeonggi-do Agricultural Drought Prediction System," which predicts agricultural weather disasters and field crop growth status.

Production of Fine-resolution Agrometeorological Data Using Climate Model

  • Ahn, Joong-Bae;Shim, Kyo-Moon;Lee, Deog-Bae;Kang, Su-Chul;Hur, Jina
    • Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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    • 2011.11a
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    • pp.20-27
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    • 2011
  • A system for fine-resolution long-range weather forecast is introduced in this study. The system is basically consisted of a global-scale coupled general circulation model (CGCM) and Weather Research and Forecast (WRF) regional model. The system makes use of a data assimilation method in order to reduce the initial shock or drift that occurs at the beginning of coupling due to imbalance between model dynamics and observed initial condition. The long-range predictions are produced in the system based on a non-linear ensemble method. At the same time, the model bias are eliminated by estimating the difference between hindcast model climate and observation. In this research, the predictability of the forecast system is studied, and it is illustrated that the system can be effectively used for the high resolution long-term weather prediction. Also, using the system, fine-resolution climatological data has been produced with high degree of accuracy. It is proved that the production of agrometeorological variables that are not intensively observed are also possible.

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Classification of Agroclimatic Zones Considering the Topography Characteristics in South Korea (지형적 특성을 고려한 우리나라의 농업기후지대 구분)

  • Kim, Yongseok;Shim, Kyo-Moon;Jung, Myung-Pyo;Choi, In-Tae;Kang, Kee-Kyung
    • Journal of Climate Change Research
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    • v.7 no.4
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    • pp.507-512
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    • 2016
  • This study was conducted to classify agroclimatic zones in South Korea. To classify the agroclimatic zones, such climatic factors as amount of rainfall from April to May, amount of rainfall in October, monthly average air temperature in January, monthly average air temperature from April to May, monthly average air temperature from April to September, monthly average air temperature from December to March, monthly minimum air temperature in January, monthly minimum air temperature from April to May, Warmth Index were considered as major influencing factors on the crop growth. Climatic factors were computed from monthly air temperature and precipitation of climatological normal year (1981~2010) at 1 km grid cell estimated from a geospatial climate interpolation method. The agroclimatic zones using k-means cluster analysis method were classified into 6 zones.

Reproduction of Long-term Memory in hydroclimatological variables using Deep Learning Model

  • Lee, Taesam;Tran, Trang Thi Kieu
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.101-101
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    • 2020
  • Traditional stochastic simulation of hydroclimatological variables often underestimates the variability and correlation structure of larger timescale due to the difficulty in preserving long-term memory. However, the Long Short-Term Memory (LSTM) model illustrates a remarkable long-term memory from the recursive hidden and cell states. The current study, therefore, employed the LSTM model in stochastic generation of hydrologic and climate variables to examine how much the LSTM model can preserve the long-term memory and overcome the drawbacks of conventional time series models such as autoregressive (AR). A trigonometric function and the Rössler system as well as real case studies for hydrological and climatological variables were tested. Results presented that the LSTM model reproduced the variability and correlation structure of the larger timescale as well as the key statistics of the original time domain better than the AR and other traditional models. The hidden and cell states of the LSTM containing the long-memory and oscillation structure following the observations allows better performance compared to the other tested conventional models. This good representation of the long-term variability can be important in water manager since future water resources planning and management is highly related with this long-term variability.

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Exploring the factors responsible for variation in streamflow using different Budyko-base functions

  • Shah, Sabab Ali;Jehanzaib, Muhammad;Kim, Min Ji;Kim, Tae-Woong
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.140-140
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    • 2022
  • Recently an accurate quantification of streamflow under various climatological and anthropogenic factors and separation of their relative contribution remains challenging, because variation in streamflow may result in hydrological disasters. In this study, we evaluated the factors responsible for variation in streamflow in Korean watersheds, quantified separately their contribution using different Budyko-based functions, and identified hydrological breakpoint points. After detecting that the hydrological break point in 1995 and time series were divided into natural period (1966-1995), and disturbed period (1996-2014). During the natural period variation in climate tended to increase change in streamflow. However, in the disturbed period both climate variation and anthropogenic activities tended to increase streamflow variation in the watershed. Subsequently, the findings acquired from different Budyko-based functions were observed sensitive to selection of function. The variation in streamflow was observed in the response of change in climatic parameters ranging 46 to 75% (average 60%). The effects of anthropogenic activities were observed less compared to climate variation accounts 25 to 54% (average 40%). Furthermore, the relative contribution was observed to be sensitive corresponding to Budyko-based functions utilized. Moreover, relative impacts of both factors have capability to enhance uncertainty in the management of water resources. Thus, this knowledge would be essential for the implementation of water management spatial and temporal scale to reduce the risk of hydrological disasters in the watershed.

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Spatial Distribution of Precipitation Trends According to Geographical and Topographical Conditions (지리지형적 조건에 따른 강수량 추세 분포)

  • Rim, Chang-Soo
    • Journal of Korea Water Resources Association
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    • v.42 no.5
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    • pp.385-396
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    • 2009
  • The spatial distribution of precipitation trends according to urbanization, geographical and topographical conditions have been studied. In this study, precipitation data from 1973 to 2006 were analyzed for 56 climatological stations including the Seoul metropolis in South Korea. In addition to annual average daily precipitation, monthly average daily precipitation in April, July, October and January were analyzed, considering seasonal effect. The geographical and topographical characteristics of these sites were examined using GIS analysis. Land use status of the study area was also examined to estimate the extent of urbanization. The study results indicate that annual average precipitation increased, and monthly average precipitation in April and October decreased, while those in January and July increased. Considering urbanization effect, annual average precipitation and monthly average precipitation in July increased; however, monthly average precipitation in January, April and October decreased. Furthermore, compared with urbanization rate and proximity to coast, average elevation of study area appeared to be the most close correlation with annual and monthly averages of precipitation trends.

Estimation of Drought Rainfall by Regional Frequency Analysis using L and LH-Moments(I) - On the Method of L-Moments - (L 및 LH-모멘트법과 지역빈도분석에 의한 가뭄우량의 추정(I) - L-모멘트법을 중심으로 -)

  • 이순혁;윤성수;맹승진;류경식;주호길
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.45 no.5
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    • pp.97-109
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    • 2003
  • This study is mainly conducted to derive the design drought rainfall by the consecutive duration using probability weighted moments with rainfall in the regional drought frequency analysis. It is anticipated to suggest optimal design drought rainfall of hydraulic structures for the water requirement and drought frequency of occurrence for the safety of water utilization through this study. Preferentially, this study was conducted to derive the optimal regionalization of the precipitation data that can be classified by the climatologically and geographically homogeneous regions all over the regions except Cheju and Ulreung islands in Korea. Five homogeneous regions in view of topographical and climatological aspects were accomplished by K-means clustering method. Using the L-moment ratio diagram and Kolmogorov-Smirnov test, generalized extreme value distribution was confirmed as the best fitting one among applied distributions. At-site and regional parameters of the generalized extreme value distribution were estimated by the method of L-moments. Design drought rainfalls using L-moments following the consecutive duration were derived by the at-site and regional analysis using the observed and simulated data resulted from Monte Carlo techniques. Relative root-mean-square error (RRMSE), relative bias (RBIAS) and relative reduction (RR) in RRMSE for the design drought rainfall derived by at-site and regional analysis in the observed an simulated data were computed and compared. In has shown that the regional frequency analysis procedure can substantially more reduce the RRMSE. RBIAS and RR in RRMSE than those of at-site analysis in the prediction of design drought rainfall. Consequently, optimal design drought rainfalls following the regions and consecutive durations were derived by the regional frequency analysis.

Drought Detection and Estimation of Water Deficit using NDVI (NDVI를 이용한 가뭄지역 검출 및 부족수분량 산정)

  • Shin, Sha-Chul;Jeong, Soo;Kim, Kyung-Tak;Kim, Joo-Hun;Park, Jung-Sool
    • Journal of the Korean Association of Geographic Information Studies
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    • v.9 no.2
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    • pp.102-114
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    • 2006
  • This study aims to develop a method to analyze droughts in Nakdong river area. Satellite imagery can be applied to droughts monitoring because it can afford periodic data for large area for long time. In this study, supposing that evapotranspiration and NDVI are closely related to each other, we presented a method to estimate evapotranspiration in large area with NDVI from MODIS data and temperature. For the final analysis of droughts, water deficit is calculated by climatological water balance using the distribution of evapotranspiration and precipitation. As the results of this study, we improved the usability of satellite imagery, especially in drought analysis.

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Study for the Changes of Annual and Seasonal Mean Temperature Using Adjusted Temperature Data in the Republic of Korea (고품질의 기온자료를 이용한 연.계절평균기온의 변화에 관한 연구)

  • Park, Chang-Yong;Choi, Young-Eun
    • Journal of the Korean Geographical Society
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    • v.46 no.1
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    • pp.20-35
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    • 2011
  • This study suggested the systematic steps for quality control, construction of the climatological reference series and homogeneity test and adjustment of temperature series in the Republic of Korea. It also attempted to evaluate more accurate magnitude of change using adjusted temperature data. All erroneous values produced by quality control were detected by internal inconsistency check. The method selected for homogeneity test in this study well defined fairly correct signals of station relocations. Therefore, this method might be regarded as the appropriate one to test homogeneity of temperature series of the Republic of Korea. The increase of temperature of the Republic of Korea after the adjustment were bigger than before the adjustment of annual and seasonal mean temperature. Adjusted temperature data produced by these steps will enable to evaluate more accurate characteristics and magnitude of climate change.

A Case Study of Tsukuba Tornado in Japan on 6 May 2012

  • Choo, Seonhee;Min, Ki-Hong;Kim, Kyung-Eak;Lee, Gyuwon
    • Journal of the Korean earth science society
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    • v.39 no.5
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    • pp.403-418
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    • 2018
  • This study conducted synoptic and mesoscale analyses to understand the cause of Japan Tsukuba tornado development, which occurred at 0340 UTC 6 May 2012. Prior to the tornado occurrence, there was a circular jet stream over Japan, and the surface was moist due to overnight precipitation. The circular jet stream brought cold and dry air to the upper-level atmosphere which let strong solar radiation heat the ground with clearing of sky cover. A tornadic supercell developed in the area of potentially unstable atmosphere. Sounding data at Tateno showed a capping inversion at 900 hPa at 0000 UTC 6 May. Strong insolation in early morning hours and removal of the inversion instigated vigorous updraft with rotation due to vertical shear in the upper-level atmosphere. This caused multiple tornadoes to occur from 0220 to 0340 UTC 6 May 2012. When comparing Tateno's climatological temperature and dew-point temperature profile on the day of event, the mid-level atmosphere was moister than typical sounding in the region. This study showed that tornado development in Tsukuba was caused by a combination of (a) topography and potential vorticity anomaly, which increased vorticity over the Kanto Plain; (b) vertical shear, which produced horizontal vortex line; and c) thermal instability, which triggered supercell and tilted the vortex line in the vertical.