• Title/Summary/Keyword: Meteorological characteristics

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Classification of Agro-Climatic Zones of the State of Mato Grosso in Brazil (브라질 마토그로소 지역의 농업기후지대 구분)

  • Jung, Myung-Pyo;Park, Hye-Jin;Hur, Jina;Shim, Kyo-Moon;Kim, Yongseok;Kang, Kee-Kyung;Ahn, Joong-Bae
    • Korean Journal of Environmental Agriculture
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    • v.38 no.1
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    • pp.34-37
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    • 2019
  • BACKGROUND: A region can be divided into agroclimatic zones based on homogeneity in weather variables that have greatest influence on crop growth and yield. The agro-climatic zone has been used to identify yield variability and limiting factors for crop growth. This study was conducted to classify agro-climatic zones in the state of Mato Grosso in Brazil for predicting crop productivity and assessing crop suitability etc. METHODS AND RESULTS: For agro-climatic zonation, monthly mean temperature, precipitation, and solar radiation data from Global Modeling and Assimilation Office (GMAO) of National Aeronautics and Space Administration (NASA, USA) between 1980 and 2010 were collected. Altitude and vegetation fraction of Brazil from Weather Research and Forecasting (WRF) were also used to classify them. The criteria of agro-climatic classification were temperature in the hottest month ($30^{\circ}C$), annual precipitation (600 mm and 1000 mm), and altitude (200 m and 500 m). The state of Mato Gross in Brazil was divided into 9 agro-climatic zones according to these criteria by using matrix classification method. CONCLUSION: The results could be useful as information for estimating agro-meteorological characteristics and predicting crop development and crop yield in the state of Mato Grosso in Brazil.

Pollution characteristics of PM2.5 observed during January 2018 in Gwangju (광주 지역에서 2018년 1월 측정한 초미세먼지의 오염 특성)

  • Yu, Geun-Hye;Park, Seung-Shik;Jung, Sun A;Jo, Mi Ra;Jang, Yu Woon;Lim, Yong Jae;Ghim, Young Sung
    • Particle and aerosol research
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    • v.15 no.3
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    • pp.91-104
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    • 2019
  • In this study, hourly measurements of $PM_{2.5}$ and its major chemical constituents such as organic and elemental carbon (OC and EC), and ionic species were made between January 15 and February 10, 2018 at the air pollution intensive monitering station in Gwangju. In addition, 24-hr integrated $PM_{2.5}$ samples were collected at the same site and analyzed for OC, EC, water-soluble OC (WSOC), humic-like substance (HULIS), and ionic species. Over the whole study period, the organic aerosols (=$1.6{\times}OC$) and $NO_3{^-}$ concentrations contributed 26.6% and 21.0% to $PM_{2.5}$, respectively. OC and EC concentrations were mainly attributed to traffic emissions with some contribution from biomass burning emissions. Moreover, strong correlations of OC with WSOC, HULIS, and $NO_3{^-}$ suggest that some of the organic aerosols were likely formed through atmospheric oxidation processes of hydrocarbon compounds from traffic emissions. For the period between January 18 and 22 when $PM_{2.5}$ pollution episode occurred, concentrations of three secondary ionic species ($=SO{_4}^{2-}+NO_3{^-}+NH_4{^+}$) and organic matter contributed on average 50.8 and 20.1% of $PM_{2.5}$, respectively, with the highest contribution from $NO_3{^-}$. Synoptic charts, air mass backward trajectories, and local meteorological conditions supported that high $PM_{2.5}$ pollution was resulted from long-range transport of haze particles lingering over northeastern China, accumulation of local emissions, and local production of secondary aerosols. During the $PM_{2.5}$ pollution episode, enhanced $SO{_4}^{2-}$ was more due to the long-range transport of aerosol particles from China rather than local secondary production from $SO_2$. Increasing rate in $NO_3{^-}$ was substantially greater than $NO_2$ and $SO{_4}^{2-}$ increasing rates, suggesting that the increased concentration of $NO_3{^-}$ during the pollution episode was attributed to enhanced formation of local $NO_3{^-}$ through heterogenous reactions of $NO_2$, rather than impact by long-range transportation from China.

Comparison of Growth Characteristics and Forage Productivity of Italian Ryegrass in Yeongseo and Yeongdong of Gangwon Province (강원 영서 및 영동지역에서 이탈리안 라이그라스 생육특성과 생산성 비교)

  • Lee, Hong-Ju;Byeon, Ji-Eun;Ryoo, Jong-Won;Hwang, Sun-Goo
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.40 no.4
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    • pp.251-258
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    • 2020
  • To investigate the suitable growing area for Italian ryegrass (cv. Kowinearly and cv. Green-Call), we survey the different effects of climatic conditions on plant growth in the east (hereafter termed Yeongdong) and west (hereafter termed Yeongseo) of the passes in Gangwon Province. The Italian ryegrass was grown in Gangneung of Yeongdong and Wonju and Chuncheon of Yeongseo. The plants showed growth differences depending on the cultivated regions between before and after wintering. The Italian ryegrass for pre-wintering showed the relatively long length of plant height in Wonju. While, we observed the relatively tall plants for growing- and harvesting-period after wintering in Gangneung. The increased plant height in Gangneung was closely related to all climatic conditions for the growing period and mean- and lowest-temperature for the harvesting period, respectively. The amount of dry matter was 7,490 kg/ha for Kowinearly and 6,490 kg/ha for Green-Call in Gangneung, which has a higher yield than Chuncheon and Wonju. The relative yield index of dry matter was 77% (Kowinearly) and 78% (Green-Call) in Chuncheon and 84% (Kowinearly) and 71% (Green-Call) in Wonju compared to Gangneung as the standard region. Thus, we suggest that Chuncheon and Wonju are the possible areas for cultivation of Italian ryegrass, considering that Gangneung was the optimum growing area in Gangwon Province.

A Statistical Correction of Point Time Series Data of the NCAM-LAMP Medium-range Prediction System Using Support Vector Machine (서포트 벡터 머신을 이용한 NCAM-LAMP 고해상도 중기예측시스템 지점 시계열 자료의 통계적 보정)

  • Kwon, Su-Young;Lee, Seung-Jae;Kim, Man-Il
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.23 no.4
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    • pp.415-423
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    • 2021
  • Recently, an R-based point time series data validation system has been established for the statistical post processing and improvement of the National Center for AgroMeteorology-Land Atmosphere Modeling Package (NCAM-LAMP) medium-range prediction data. The time series verification system was used to compare the NCAM-LAMP with the AWS observations and GDAPS medium-range prediction model data operated by Korea Meteorological Administration. For this comparison, the model latitude and longitude data closest to the observation station were extracted and a total of nine points were selected. For each point, the characteristics of the model prediction error were obtained by comparing the daily average of the previous prediction data of air temperature, wind speed, and hourly precipitation, and then we tried to improve the next prediction data using Support Vector Machine( SVM) method. For three months from August to October 2017, the SVM method was used to calibrate the predicted time series data for each run. It was found that The SVM-based correction was promising and encouraging for wind speed and precipitation variables than for temperature variable. The correction effect was small in August but considerably increased in September and October. These results indicate that the SVM method can contribute to mitigate the gradual degradation of medium-range predictability as the model boundary data flows into the model interior.

Changes in the Spatiotemporal Patterns of Precipitation Due to Climate Change (기후변화에 따른 강수량의 시공간적 발생 패턴의 변화 분석)

  • Kim, Dae-Jun;Kang, DaeGyoon;Park, Joo-Hyeon;Kim, Jin-Hee;Kim, Yongseok
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.23 no.4
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    • pp.424-433
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    • 2021
  • Recent climate change has caused abnormal weather phenomena all over the world and a lot of damage in many fields of society. Particularly, a lot of recent damages were due to extreme precipitation, such as torrential downpour or drought. The objective of this study was to analyze the temporal and spatial changes in the precipitation pattern in South Korea. To achieve this objective, this study selected some of the precipitation indices suggested in previous studies to compare the temporal characteristics of precipitation induced by climate change. This study selected ten ASOS observatories of the Korea Meteorological Administration to understand the change over time for each location with considering regional distribution. This study also collected daily cumulative precipitation from 1951 to 2020 for each point. Additionally, this study generated high-resolution national daily precipitation distribution maps using an orographic precipitation model from 1981 to 2020 and analyzed them. Temporal analysis showed that although annual cumulative precipitation revealed an increasing trend from the past to the present. The number of precipitation days showed a decreasing trend at most observation points, but the number of torrential downpour days revealed an increasing trend. Spatially, the number of precipitation days and the number of torrential downpour days decreased in many areas over time, and this pattern was prominent in the central region. The precipitation pattern of South Korea can be summarized as the fewer precipitation days and larger daily precipitation over time.

A Study on the Predictability of the Number of Days of Heat and Cold Damages by Growth Stages of Rice Using PNU CGCM-WRF Chain in South Korea (PNU CGCM-WRF Chain을 이용한 남한지역 벼의 생육단계별 고온해 및 저온해 발생일수에 대한 예측성 연구)

  • Kim, Young-Hyun;Choi, Myeong-Ju;Shim, Kyo-Moon;Hur, Jina;Jo, Sera;Ahn, Joong-Bae
    • Atmosphere
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    • v.31 no.5
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    • pp.577-592
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    • 2021
  • This study evaluates the predictability of the number of days of heat and cold damages by growth stages of rice in South Korea using the hindcast data (1986~2020) produced by Pusan National University Coupled General Circulation Model-Weather Research and Forecasting (PNU CGCM-WRF) model chain. The predictability is accessed in terms of Root Mean Square Error (RMSE), Normalized Standardized Deviations (NSD), Hit Rate (HR) and Heidke Skill Score (HSS). For the purpose, the model predictability to produce the daily maximum and minimum temperatures, which are the variables used to define heat and cold damages for rice, are evaluated first. The result shows that most of the predictions starting the initial conditions from January to May (01RUN to 05RUN) have reasonable predictability, although it varies to some extent depending on the month at which integration starts. In particular, the ensemble average of 01RUN to 05RUN with equal weighting (ENS) has more reasonable predictability (RMSE is in the range of 1.2~2.6℃ and NSD is about 1.0) than individual RUNs. Accordingly, the regional patterns and characteristics of the predicted damages for rice due to excessive high- and low-temperatures are well captured by the model chain when compared with observation, particularly in regions where the damages occur frequently, in spite that hindcasted data somewhat overestimate the damages in terms of number of occurrence days. In ENS, the HR and HSS for heat (cold) damages in rice is in the ranges of 0.44~0.84 and 0.05~0.13 (0.58~0.81 and -0.01~0.10) by growth stage. Overall, it is concluded that the PNU CGCM-WRF chain of 01RUN~05RUN and ENS has reasonable capability to predict the heat and cold damages for rice in South Korea.

Feasibility Study for Derivation of Tropospheric Ozone Motion Vector Using Geostationary Environmental Satellite Measurements (정지궤도 위성 대류권 오존 관측 자료를 이용한 대류권 이동벡터 산출 가능성 연구)

  • Shin, Daegeun;Kim, Somyoung;Bak, Juseon;Baek, Kanghyun;Hong, Sungjae;Kim, Jaehwan
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1069-1080
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    • 2022
  • The tropospheric ozone is a pollutant that causes a great deal of damage to humans and ecosystems worldwide. In the event that ozone moves downwind from its source, a localized problem becomes a regional and global problem. To enhance ozone monitoring efficiency, geostationary satellites with continuous diurnal observations have been developed. The objective of this study is to derive the Tropospheric Ozone Movement Vector (TOMV) by employing continuous observations of tropospheric ozone from geostationary satellites for the first time in the world. In the absence of Geostationary Environmental Monitoring Satellite (GEMS) tropospheric ozone observation data, the GEOS-Chem model calculated values were used as synthetic data. Comparing TOMV with GEOS-Chem, the TOMV algorithm overestimated wind speed, but it correctly calculated wind direction represented by pollution movement. The ozone influx can also be calculated using the calculated ozone movement speed and direction multiplied by the observed ozone concentration. As an alternative to a backward trajectory method, this approach will provide better forecasting and analysis by monitoring tropospheric ozone inflow characteristics on a continuous basis. However, if the boundary of the ozone distribution is unclear, motion detection may not be accurate. In spite of this, the TOMV method may prove useful for monitoring and forecasting pollution based on geostationary environmental satellites in the future.

Enhanced Primary Production in Response to Freshwater Inflow in the Nakdong River Estuary: Characteristics of land-Ocean Coupling (LOC) (낙동강 하구에서 담수 유입에 따른 연안 클로로필-a 증가 : 낙동강의 육상-해양 coupling 패턴 분석)

  • KIM, SUHYUN;AN, SOONMO
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.26 no.2
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    • pp.96-109
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    • 2021
  • Since terrestrial input plays a major role in coastal primary production, an understanding of land-ocean coupling (LOC) is key to understand coastal ecological changes. In this study, the LOC has been classified into three stages (i.e., the baseflow, plume event and residual flow). In order to characterize its pattern in Nakdong River estuary, multi-platform data were obtained from remote sensing (geostationary ocean color image (GOCI)), in-situ measurement (marine environment information system (MEIS)), on-site measurement (discharge data and meteorological data). The MEIS data were grouped into three stages of LOC using principal component analysis (PCA), and the LOC (2013 ~ 2018) was examined at each stage using multi-platform data. In the Nakdong River estuary, the maximum value of chlorophyll-a (chl-a) was unexpectedly appeared during the plume event. It is assumed that there was no significant increase in turbidity, expected during the typical plume event, together with the weak flushing effect, caused the enhanced phytoplankton growth. Compared with other estuaries, LOC is common in estuaries affected by freshwater inflow, but LOC has different pattern depending on the size of the plume. While estuaries that form small plumes of about 10 km (low freshwater discharge and weak flushing effect) observed high chl-a in the plume event because the phytoplankton can response to the increased nutrient more rapidly. estuaries that form large plumes of more than 100 km est (high freshwater discharge and strong flushing effect) follow the typical LOC pattern conceptualized in this study (high chl-a in the residual flow).

Sensitivity Analysis of Drought Impact Factors Using a Structural Equation Model and Bayesian Networks (구조방정식모형과 베이지안 네트워크를 활용한 가뭄 영향인자의 민감도 분석)

  • Kim, Ji Eun;Kim, Minji;Yoo, Jiyoung;Jung, Sungwon;Kim, Tae-Woong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.42 no.1
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    • pp.11-21
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    • 2022
  • Drought occurs extensively over a long period and causes great socio-economic damage. Since drought risk consists of social, environmental, physical, and economic factors along with meteorological and hydrological factors, it is important to quantitatively identify their impacts on drought risk. This study investigated the relationship among drought hazard, vulnerability, response capacity, and risk in Chungcheongbuk-do using a structural equation model and evaluated their impacts on drought risk using Bayesian networks. We also performed sensitivity analysis to investigate how the factors change drought risk. Overall results showed that Chungju-si had the highest risk of drought. The risk was calculated as the largest even when the hazard and response capacity were changed. However, when the vulnerability was changed, Eumseong-gun had the greatest risk. The sensitivity analysis showed that Jeungpyeong-gun had the highest sensitivity, and Jecheon-si, Eumseong-gun, and Okcheon-gun had highest individual sensitivities with hazard, vulnerability, and response capacity, respectively. This study concluded that it is possible to identify impact factors on drought risk using regional characteristics, and to prepare appropriate drought countermeasures considering regional drought risk.

A study on the rainfall-runoff reduction efficiency on each design rainfall for the green infrastructure-baesd stormwater management (그린인프라 기반 빗물 관리를 위한 설계강우량별 강우-유출저감 효율성 분석 연구)

  • Kim, Byungsung;Kim, Jaemoon;Lee, Sangjin
    • Journal of Korea Water Resources Association
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    • v.55 no.8
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    • pp.613-621
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    • 2022
  • Due to the global climate change, the rainfall volume and frequency on the Korean Peninsula are predicted to increase at the end of the 21st century. In addition, impervious surface areas have increased due to rapid urbanization which has caused the urban water cycle to deteriorate. Green Infrastructure (GI) researches have been conducted to improve the water cycle soundness; the efficiency of this technique has been verified through various studies. However, there are still no suitable GI design guidelines for this aspect. Therefore, the rainfall scenarios are set up for each percentile (60, 70, 80, 90) based on the volume and frequency analysis using 10-year rainfall data (Busan Meteorological Station). After determining the GI areas for each scenario, the runoff reduction characteristics are analyzed based on Storm Water Management Model (SWMM) 10-year rainfall-runoff-simulations. The total runoff reduction efficiency for each GI areas are computed to have a range of 13.1~52.1%. As a results of the quantitative analysis, the design rainfall for GI is classified into the 80~85 percentile in the study site.