• The Plant Pathology Journal
• /
• v.35 no.5
• /
• pp.459-472
• /
• 2019

The increasing variation in climatic conditions under climate change directly influences plant-microbe interactions. To account for as many variables as possible that may play critical roles in such interactions, the use of an integrated modeling approach is necessary. Here, we report for the first time a local impact assessment and adaptation study of future epidemics of kiwifruit bacterial blossom blight (KBB) in Jeonnam province, Korea, using an integrated modeling approach. This study included a series of models that integrated both the phenological responses of kiwifruit and the epidemiological responses of KBB to climatic factors with a 1 km resolution, under the RCP8.5 climate change scenario. Our results indicate that the area suitable for kiwifruit cultivation in Jeonnam province will increase and that the flowering date of kiwifruit will occur increasingly earlier, mainly due to the warming climate. Future epidemics of KBB during the predicted flowering periods were estimated using the Pss-KBB Risk Model over the predicted suitable cultivation regions, and we found location-specific, periodic outbreaks of KBB in the province through 2100. Here, we further suggest a potential, scientifically-informed, long-term adaptation strategy using a cultivar of kiwifruit with a different maturity period to relieve the pressures of future KBB risk. Our results clearly show one of the possible options for a local impact assessment and adaptation study using multiple models in an integrated way.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.65 no.1
• /
• pp.1-13
• /
• 2023

Various techniques for bias correction and statistical downscaling have been developed to overcome the limitations related to the spatial and temporal resolution and error of climate change scenario data required in various applied research fields including agriculture and water resources. In this study, the characteristics of three different statistical dowscaling methods (i.e., SQM, SDQDM, and BCSA) provided by AIMS were summarized, and climate change scenarios produced by applying each method were comparatively evaluated. In order to compare the average rainfall characteristics of the past period, an index representing the average rainfall characteristics was used, and the reproducibility of extreme weather conditions was evaluated through the abnormal climate-related index. The reproducibility comparison of spatial distribution and variability was compared through variogram and pattern identification of spatial distribution using the average value of the index of the past period. For temporal reproducibility comparison, the raw data and each detailing technique were compared using the transition probability. The results of the study are presented by quantitatively evaluating the strengths and weaknesses of each method. Through comparison of statistical techniques, we expect that the strengths and weaknesses of each detailing technique can be represented, and the most appropriate statistical detailing technique can be advised for the relevant research.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2015.05a
• /
• pp.20-20
• /
• 2015

최근 기후변화의 영향으로 전 세계적으로 홍수와 가뭄의 발생빈도가 증가하고 있다. 특히, 가뭄은 우리나라에서 겨울과 봄철을 중심으로 매년 발생되고 있다. 가뭄의 정확한 발생을 판단하기는 어려우나, 가뭄이 발생되면 그 진행속도는 홍수보다 느리기 때문에 초기에 가뭄의 발생가능성을 예측한다면 가뭄에 대한 피해를 줄일 수 있다. 따라서 최근 가뭄 예측에 대한 다양한 연구가 이루어지고 있다. 본 연구에서는 가뭄발생의 불확실성을 내포하기 위하여 Bayesian Network (BN) 모형과 SPI의 자기상관성을 바탕으로 가까운 미래의 가뭄 발생확률을 예측하는 방법을 제안하였다. BN은 변수들 간의 인과관계를 확률적으로 나타낼 수 있는 네트워크 모형으로, 자연현상에 대한 위험도 분석 및 의학 분야에서 질병추정을 위한 모형으로 활용되고 있다. 본 연구에서는 가까운 미래의 가뭄 예측을 위하여 APEC 기후센터(APEC Climate Center, APCC)에서 제공하는 다중모형앙상블(Multi-model Ensemble, MME) 강우예측 결과로 도출한 미래 SPI 및 과거 강우량 자료로 구축한 SPI를 부모노드로, 예측 SPI를 자식노드로 BN을 구축하였다. BN의 각각의 노드를 Gaussian 확률분포모형으로 가정한 뒤, Likelihood weighting 방법으로 주변사후분포확률(Marginal posterior distribution)을 추정하여 미래의 SPI의 발생확률을 계산하였다. 2008년부터 2013년의 BN 가뭄 예측값과 MME 강우예측 결과로 도출한 SPI를 실제 관측 강우량으로 산정한 SPI와 비교하였으며, BN이 실제 관측결과에 가까운 결과가 도출되었다. 본 연구에서는 BN을 활용하여 가까운 미래의 가뭄 발생가능성을 확률적으로 나타낼 수 있는 방법을 제시하였으며, 그 결과 가뭄상태별 가뭄 발생확률이 산정되었다.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.34 no.4
• /
• pp.1125-1138
• /
• 2014

In this study, we applied an advanced non-parametric low-flow frequency analysis using boundary kernel by Representative Concentration Pathways (RCPs) climate change scenarios through Arc-SWAT long-term runoff model simulation at the Gwangdong storage reservoir located in Taeback, Gangwondo. The results show that drought frequency under RCPs was expected to increase due to reduced runoff during the near future, and the variation of low-flow time series was appeared greatly under RCP8.5 scenario, respectively. The result from drought frequency of Median flow in the near future (2030s) compared historic period, the case of 30-year low-flow frequency was increased (the RCP4.5 shows +22.4% and the RCP8.5 shows +40.4%), but in the distant future (2080s) expected increase of drought frequency due to the reduction of low-flow (under RCP4.5: -4.7% and RCP8.5: -52.9%), respectively. In case of Quantile 25% flow time series data also expected that the severe drought frequency will be increased in the distant future by reducing low-flow (the RCP4.5 shows -20.8% to -60.0% and the RCP8.5 shows -30.4% to -96.0%). This non-parametric low-flow frequency analysis results according to the RCPs scenarios have expected to consider to take advantage of as a basis data for water resources management and countermeasures of climate change in the mid-watershed over the Korean Peninsula.

• Atmosphere
• /
• v.27 no.3
• /
• pp.345-358
• /
• 2017

The decadal change in rainfall for Changma period over the South Korea in early-2000s is detected in this study. The Changma rainfall in P1 (1992~2002) decade is remarkably less than in P2 (2003~2013) decade. The much rainfall in P2 decade is associated with the increase of rainy day frequency during Changma period, including the frequent occurrences of rainy day with a intensity of 30 mm/day or more in P2 decade. This decadal change in the Changma rainfall is due to the decadal change of atmospheric circulation around the Korean Peninsula which affects the intensity and location of Changma rainfall. During P2 decade, the anomalous anti-cyclone over the south of the Korean Peninsula, which represents the expansion of the North Pacific high with warm and wet air mass toward East Asia, is stronger than in P1 decade. In addition, the upper level zonal wind and meridional gradient of low-level equivalent potential temperature in P2 decade is relatively strengthened over the northern part of the Korean Peninsula than in P1 decade, which corresponds with the intensification of meridional gradient between air mass related to the East Asian summer monsoon nearby the Korean Peninsula in P2 decade. The enhanced meridional gradient of atir mass during P2 decade is favorable condition for the intensification of Changma rainfall band and more Changma rainfall. The atmospheric conditions related to enhanced Changma rainfall during P2 decade is likely to be influenced by the teleconnection linked to the suppressed convection anomaly over the southern part of China and South China Sea in P2 decade.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.57 no.5
• /
• pp.1-12
• /
• 2015

The study aimed to project inflows and demmands for the agricultural reservoir watersheds in South Korea considering a variety of regional characteristics and the uncertainty of future climate information. The study bias-corrected and spatially downscaled retrospective daily Global Climate Model (GCM) outputs under Representative Concentration Pathways (RCP) 4.5 and 8.5 emission scenarios using non-parametric quantile mapping method to force Soil and Water Assessment Tool (SWAT) model. Using the historical simulation, the skills of un-calibrated SWAT model (without calibration process) was evaluated for 5 reservoir watersheds (selected as well-monitored representatives). The study then, evaluated the performance of 9 GCMs in reproducing historical upstream inflow and irrigation demand at the five representative reservoirs. Finally future inflows and demands for 58 watersheds were projected using 9 GCMs projections under the two RCP scenarios. We demonstrated that (1) un-calibrated SWAT model is likely applicable to agricultural watershed, (2) the uncertainty of future climate information from different GCMs is significant, (3) multi-model ensemble (MME) shows comparatively resonable skills in reproducing water balances over the study area. The results of projection under the RCP 4.5 and RCP 8.5 scenario generally showed the increase of inflow by 9.4% and 10.8% and demand by 1.4% and 1.7%, respectively. More importantly, the results for different seasons and reservoirs varied considerably in the impacts of climate change.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
• /
• 2011.11a
• /
• pp.20-27
• /
• 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.

• The Plant Pathology Journal
• /
• v.35 no.1
• /
• pp.1-10
• /
• 2019

Wheat blast occurred in Bangladesh for the first time in Asia in 2016. It is caused by a fungal pathogen, Magnaporthe oryzae Triticum (MoT) pathotype. In this review, we focused on the current status of the wheat blast in regard to host, pathogen, and environment. Despite the many efforts to control the disease, it expanded to neighboring regions including India, the world's second largest wheat producer. However, the disease occurrence has definitely decreased in quantity, because of many farmers chose to grow alternate crops according to the government's directions. Bangladesh government planned to introduce blast resistant cultivars but knowledges about genetics of resistance is limited. The genome analyses of the pathogen population revealed that the isolates caused wheat blast in Bangladesh are genetically close to a South American lineage of Magnaporthe oryzae. Understanding the genomes of virulent strains would be important to find target resistance genes for wheat breeding. Although the drier winter weather in Bangladesh was not favorable for development of wheat blast before, recent global warming and climate change are posing an increasing risk of disease development. Bangladesh outbreak in 2016 was likely to be facilitated by an extraordinary warm and humid weather in the affected districts before the harvest season. Coordinated international collaboration and steady financial supports are needed to mitigate the fearsome wheat blast in South Asia before it becomes a catastrophe.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2020.06a
• /
• pp.195-195
• /
• 2020

이 연구는 기후변화 위험에 노출되어 있는 북한에 대한 잠재증발산량의 미래 변화를 전망하였다. 이를 위해 IPCC AR5의 RCP 기후변화 시나리오로부터 모의된 미래 기온자료를 APCC (APEC Climate Center) Integrated Modeling (AIMS)를 사용하여 25개 관측 지점에 대해서 상세화하여, McGuinness-Borne 방법으로 잠재증발산량을 추정하였다. 6개의 성능 지표와 TOPSIS(Technique for Order of Preference by Similarity to Ideal Solution)로 27개 GCMs 간의 과거 기후 재현성을 비교하여, 관측 지점 규모에서 적정 GCM을 선정하였다. 마지막으로 각 지점에서 선정된 대표 시나리오(representative climate change scenarios, RCCS)로 북한 지역의 잠재증발산량의 미래 변화를 3개의 구간(F1: 2011-2040; F2: 2041-2070; F3: 2071-2100)에서 all CCS(climate change scenario)와 비교하고, 미래 변화를 정량적으로 제시하였다. 그 결과 공간 해상도가 더 높은 GCM이 RCCS로 선정되었으며, 미래로 갈수록 잠재증발산량이 증가하리라 전망되었다. 또한, 여름철 잠재증발산량의 모델 간 변동성은 미래 구간에 따라 점진적으로 증가되었고, 연 평균 증발산량은 과거 기후대비 1.4배(F1), 2.0배(F2) 및 2.6배(F3) 증가하였다.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
• /
• 2014.10a
• /
• pp.1-24
• /
• 2014

This study uses geo-spatial crop modeling to quantify the biophysical impact of weather extremes. More specifically, the study analyzes the weather extreme which affected maize production in the USA in 2012; it also estimates the effect of a similar weather extreme in 2050, using future climate scenarios. The secondary impact of the weather extreme on food security in the developing world is also assessed using trend analysis. Many studies have reported on the significant reduction in maize production in the USA due to the extreme weather event (combined heat wave and drought) that occurred in 2012. However, most of these studies focused on yield and did not assess the potential effect of weather extremes on food prices and security. The overall goal of this study was to use geo-spatial crop modeling and trend analysis to quantify the impact of weather extremes on both yield and, followed food security in the developing world. We used historical weather data for severe extreme events that have occurred in the USA. The data were obtained from the National Climatic Data Center (NCDC) of the National Oceanic and Atmospheric Administration (NOAA). In addition we used five climate scenarios: the baseline climate which is typical of the late 20th century (2000s) and four future climate scenarios which involve a combination of two emission scenarios (A1B and B1) and two global circulation models (CSIRO-Mk3.0 and MIROC 3.2). DSSAT 4.5 was combined with GRASS GIS for geo-spatial crop modeling. Simulated maize grain yield across all affected regions in the USA indicates that average grain yield across the USA Corn Belt would decrease by 29% when the weather extremes occur using the baseline climate. If the weather extreme were to occur under the A1B emission scenario in the 2050s, average grain yields would decrease by 38% and 57%, under the CSIRO-Mk3.0 and MIROC 3.2 global climate models, respectively. The weather extremes that occurred in the USA in 2012 resulted in a sharp increase in the world maize price. In addition, it likely played a role in the reduction in world maize consumption and trade in 2012/13, compared to 2011/12. The most vulnerable countries to the weather extremes are poor countries with high maize import dependency ratios including those countries in the Caribbean, northern Africa and western Asia. Other vulnerable countries include low-income countries with low import dependency ratios but which cannot afford highly-priced maize. The study also highlighted the pathways through which a weather extreme would affect food security, were it to occur in 2050 under climate change. Some of the policies which could help vulnerable countries counter the negative effects of weather extremes consist of social protection and safety net programs. Medium- to long-term adaptation strategies include increasing world food reserves to a level where they can be used to cover the production losses brought by weather extremes.