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

• Atmosphere
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• v.33 no.2
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• pp.223-246
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• 2023

This paper summarized the research papers on weather extremes that occurred in the Republic of Korea, which were published in the domestic and foreign journals during 1963~2022. Weather extreme is defined as a weather phenomenon that causes serious casualty and property loss; here, it includes typhoon, heavy rain, drought, heat wave, cold surge, heavy snow, and strong gust. Based on the 2011~2020 statistics in Korea, above 80% of property loss due to all natural disasters were caused by typhoons and heavy rainfalls. However, the impact of the other weather extremes can be underestimated rather than we have actually experienced; the property loss caused by the other extremes is hard to be quantitatively counted. Particularly, as global warming becomes serious, the influence of drought and heat wave has been increasing. The damages caused by cold surges, heavy snow, and strong gust occurred over relatively local areas on short-term time scales compared to other weather hazards. In particularly, strong gust accompanied with drought may result in severe forest fires over mountainous regions. We hope that the present review paper may remind us of the importance of weather extremes that directly affect our lives.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2003.09a
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• pp.161-178
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• 2003

Agriculture is probably the most weather-dependent of all human activities. Variations lil climate have been, and continue to be, the principal source of fluctuations in global food production, particularly in the semi-arid tropical countries of the developing world. Throughout history, extremes of heat and cold, droughts and floods, and various forms of violent weather have wreaked havoc on the agricultural systems that depend on for food.(omitted)

• The Korean Journal of Applied Statistics
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• v.22 no.1
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• pp.221-235
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• 2009

This manuscript illustrates the comparative study between ARIMA and Exponential Smoothing modeling to develop forest fire forecasting system using different weather parameters. In this paper, authors have developed the most suitable and closest forecasting models like ARIMA and Exponential Smoothing techniques using different weather parameters. Authors have considered the extremes of the Wind speed, Radiation, Maximum Temperature and Deviation Temperature of the Summer Season form March to June month for the Ranchi Region in Jharkhand. The data is taken by own resource with the help of Automatic Weather Station. This paper consists a deep study of the effect of extreme values of the different parameters on the weather fluctuations which creates forest fires in the region. In this paper, the numerical illustration has been incorporated to support the present study. Comparative study of different suitable models also incorporated and best fitted model has been tested for these parameters.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.403-417
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• 2014

Increased frequency of climate extremes is another face of climate change confronted by humans, resulting in catastrophic losses in agriculture. While climate extremes take place on many scales, impacts are experienced locally and mitigation tools are a function of local conditions. To address this, agrometeorological early warning systems must be place and location based, incorporating the climate, crop and land attributes at the appropriate scale. Existing services often lack site-specific information on adverse weather and countermeasures relevant to farming activities. Warnings on chronic long term effects of adverse weather or combined effects of two or more weather elements are seldom provided, either. This lecture discusses a field-specific early warning system implemented on a catchment scale agrometeorological service, by which volunteer farmers are provided with face-to-face disaster warnings along with relevant countermeasures. The products are based on core techniques such as scaling down of weather information to a field level and the crop specific risk assessment. Likelihood of a disaster is evaluated by the relative position of current risk on the standardized normal distribution from climatological normal year prepared for 840 catchments in South Korea. A validation study has begun with a 4-year plan for implementing an operational service in Seomjin River Basin, which accommodates over 60,000 farms and orchards. Diverse experiences obtained through this study will certainly be useful in planning and developing the nation-wide disaster early warning system for agricultural sector.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2014.10a
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• pp.25-48
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• 2014

Increased frequency of climate extremes is another face of climate change confronted by humans, resulting in catastrophic losses in agriculture. While climate extremes take place on many scales, impacts are experienced locally and mitigation tools are a function of local conditions. To address this, agrometeorological early warning systems must be place and location based, incorporating the climate, crop and land attributes at the appropriate scale. Existing services often lack site-specific information on adverse weather and countermeasures relevant to farming activities. Warnings on chronic long term effects of adverse weather or combined effects of two or more weather elements are seldom provided, either. This lecture discusses a field-specific early warning system implemented on a catchment scale agrometeorological service, by which volunteer farmers are provided with face-to-face disaster warnings along with relevant countermeasures. The products are based on core techniques such as scaling down of weather information to a field level and the crop specific risk assessment. Likelihood of a disaster is evaluated by the relative position of current risk on the standardized normal distribution from climatological normal year prepared for 840 catchments in South Korea. A validation study has begun with a 4-year plan for implementing an operational service in Seomjin River Basin, which accommodates over 60,000 farms and orchards. Diverse experiences obtained through this study will certainly be useful in planning and developing the nation-wide disaster early warning system for agricultural sector.

• The Korean Journal of Applied Statistics
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• v.27 no.4
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• pp.655-665
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• 2014

An adequate understanding and response to natural hazards such as heat wave, heavy rainfall and severe drought is required. We apply extreme value theory to analyze these abnormal weather phenomena. It is common for extremes in climatic data to be nonstationary in space and time. In this paper, we analyze summer rainfall data in South Korea using exceedance values over thresholds estimated by quantile regression with location information and time as covariates. We group weather stations in South Korea into 5 clusters and t extreme value models to threshold exceedances for each cluster under the assumption of independence in space and time as well as estimates of uncertainty for spatial dependence as proposed in Northrop and Jonathan (2011).

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.23-30
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• 2021

In recent years, hazardous flash flooding has caused deaths and damage to infrastructure in Saudi Arabia. In this paper, our aim is to assess patterns and trends in climate means and extremes affecting flash flood hazards and water resources in Saudi Arabia for the purpose to improve risk assessment for forecast capacity. We would like to examine temperature, precipitation climatology and trend magnitudes at surface stations in Saudi Arabia. Based on the assessment climate patterns maps and trends are accurately used to identify synoptic situations and tele-connections associated with flash flood risk. We also study local and regional changes in hydro-meteorological extremes over recent decades through new applications of statistical methods to weather station data and remote sensing based precipitation products; and develop remote sensing based high-resolution precipitation products that can aid to develop flash flood guidance system for the flood-prone areas. A dataset of extreme events has been developed using the multi-decadal station data, the statistical analysis has been performed to identify tele-connection indices, pressure and sea surface temperature patterns most predictive to heavy rainfall. It has been combined with time trends in extreme value occurrence to improve the potential for predicting and rapidly detecting storms. A methodology and algorithms has been developed for providing a well-calibrated precipitation product that can be used in the early warning systems for elevated risk of floods.

• The Journal of Bigdata
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• v.2 no.2
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• pp.129-140
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• 2017

Weather acts through low visibility, precipitation, high winds, and temperature extremes to affect driver capabilities, vehicle performance (i.e., traction, stability and maneuverability), pavement friction, roadway infrastructure, crash risk, traffic flow, and agency productivity. Recently a variety of road weather big data sources such as CCTV, road sensor/systems, car sensor have been developed to solve the weather-related problems, This study identifies and defines the types and characteristics of these sources to suggest how to utilize them for car safety and efficiency as well as road management through analyzing domestic and oversea cases of road weather big data applications.

• The Plant Pathology Journal
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• v.31 no.3
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• pp.290-298
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• 2015

Starting in 2012, severe diebacks usually accompanied by abundant gum exudation have occurred on yuzu trees in Goheung-gun, Jeonnam Province, where severely affected trees were occasionally killed. On-farm surveys were conducted at 30 randomly-selected orchards located at Pungyang-myeon, Goheung-gun, and the resulting disease incidences were 18.5% and 39.6% for dieback and gumming symptoms, respectively. Black spots on branches and leaves also appeared on infected trees showing a typical dieback symptom. Morphological and molecular identifications of the isolated fungal organisms from lesions on the symptomatic leaves and branches revealed that they are identical to Phomopsis citri, known to cause gummosis. In order to find the reason for this sudden epidemic, we investigated the weather conditions that are exclusively distinct from previous years, hypothesizing that certain weather extremes might have caused the severe induction of pre-existing disease for yuzu. There were two extreme temperature drops beyond the yuzu's cold hardiness limit right after an abnormally-warm-temperature-rise during the winter of 2011-12, which could cause severe frost damage resulting in mechanical injuries and physiological weakness to the affected trees. Furthermore, there was an increased frequency of strong wind events, seven times in 2012 compared to only a few times in the previous years, that could also lead to extensive injuries on branches. In conclusion, we estimated that the possible damages by severe frost and frequent strong wind events during 2012 could cause the yuzu trees to be vulnerable to subsequent fungal infection by providing physical entries and increasing plant susceptibility to infections.