기후변화 취약성 지수 산출을 위한 한반도 관측 기후 특성 분석

남기표,강정언,김철희 한국환경영향평가학회 2011 환경영향평가 Vol.20 No.6

Climate vulnerability index is usually defined as a function of the climate exposure, sensitivity, and adaptive capacity, which requires adequate selection of proxy variables of each variable. We selected and used 9 proxy variables related to climate exposure in the literature, and diagnosed the adequacy of them for application in Korean peninsula. The selected proxy variables are: four variables from temperature, three from precipitation, one from wind speed, and one from relative humidity. We collected climate data over both previous year (1981~2010) and future climate scenario (A1B scenario of IPCC SERES) for 2020, 2050, and 2100. We introduced the spatial and temporal diagnostic statistical parameters, and evaluated both spatial and time variabilities in the relative scale. Of 9 proxy variables, effective humidity indicated the most sensitive to climate change temporally with the biggest spatial variability, implying a good proxy variable in diagnostics of climate change vulnerability in Korea. The second most sensitive variable is the frequency of strong wind speed with a decreasing trend, suggesting that it should be used carefully or may not be of broad utility as a proxy variable in Korea. The A1B scenario of future climate in 2020, 2050 and 2100 matches well with the extension of linear trend of observed variables during 1981~2010, indicating that, except for strong wind speed, the selected proxy variables can be effectively used in calculating the vulnerability index for both past and future climate over Korea. Other local variabilities for the past and future climate in association with climate exposure variables are also discussed here.

Observed and simulated climate variability and trends in a semiarid region

Sri Lakshmi Sesha Vani Jayanthi,Venkata Reddy Keesara 대한공간정보학회 2020 Spatial Information Research Vol.28 No.1

Understanding climate variability under various climate scenarios is essential to predict the adverse impacts of climate change. Climate variability is often assessed by detection and estimation of trends in the observed and future climate variables. The objective of this study is to determine the trends in precipitation (PCP), minimum and maximum temperature (TMAX, TMIN) in Telangana, India which is a semi-arid region. To assess the observed climate trends, gridded rainfall and temperature data obtained from the Indian Meteorological Department (IMD) for 63 years (1951–2013) are used in the present study. The future climate scenarios for Telangana are assessed using the regional climate model data obtained from Coordinated Regional Climate Downscaling Experiment under RCP 4.5 and RCP 8.5 for 31 years (2020–2050). Climate variability is assessed by calculating co-efficient of variation, parametric (linear regression) and non-parametric tests (Mann–Kendall and Sen’s Slope) are employed at each grid point to determine the possible trends in the climate. The results exhibit a significant increasing trend in for both TMAX and TMIN observed data. Whereas, the daily PCP exhibits no specific pattern indicating uncertainty in precipitation. For the future period, RCP 4.5 scenario shows an increasing trend for PCP and TMAX, while decreasing trend is observed for TMIN. RCP 8.5 scenario results show a decreasing trend for PCP and increasing trends for both TMAX and TMIN.

생물종 분포모델에 미치는 기후·지형인자의 영향 분석

김태근(Tae Geun Kim),정종철(Jong-Chul Jeong) 국립공원연구원 2013 국립공원연구지 Vol.4 No.1

본 연구에서는 생물종에 대한 지리적 분포를 예측하는데 널리 활용되고 있는 생태적 지위개념을 기반으로 하는 생물종 분포모델의 정확도에 미치는 기후·지형인자의 영향력을 분석하고자 한다. 오대산국립공원의 아고산 지역에서 조사된 외래식물을 대상으로 기후변수로는 기온과 강수량을 이용하고 지형변수로는 해발고도, 경사, 사면, 지형습윤지수, 그리고 하천유량을 예측변수로 하고 이들 조합에 의한 생물종분포 모델에 미치는 영향을 평가하고자 한다. 이는 최근 생태분야에서 널리 활용되고 검증된 최대 엔트로피(Maximum entropy, Maxent) 알고리즘을 적용한 종 분포 모델의 수행 결과를 ROC의 AUC 값(Area Under Curve of Receiver Operating Characteristic)을 통한 모델 정확도와 모델 별 외래식물의 최대 출현가능성을 비교하고 예측된 외래식물의 분포지역에 현지 조사된 지점이 얼마나 포함되는지에 대한 점유율을 이용하여 평가하였다. 모델 정확도는 생물기후학적 변수 및 지형적인 변수만을 고려한 경우보다 두 변수를 동시에 적용한 경우가 세 가지 모델 정확도 중에서 AUC 값이 0.997로 모델 간 유의적인 차이는 나타나지 않았지만 가장 높게 산출되었고 최대출현가능성도 가장 높은 99.5%의 예측 결과가 나타났다. 또한, 외래식물의 출현가능성이 50% 이상일 경우를 외래식물의 잠재적 분포지역으로 하여 면적을 비교한 결과를 보면 기후 및 지형 변수를 동시에 고려한 경우에서 면적이 4,174 ㎢로 가장 작은 분포지역이 예측되었다. 이는 모델의 예측결과를 설명하는 변수의 유형이나 개수에 민감하지 않고 안정화된 결과를 보여주고 외래식물의 분포는 단순적인 환경특성보다는 기후 및 지형 등과 같은 복합적인 특성에 기인한다는 사실을 간접적으로 보여주는 결과라 할 수 있다. 결과적으로 Maxent 알고리즘을 다양한 환경변수에 적용한 모델은 국립공원에 서식하는 다양한 생물종의 잠재적인 분포지역을 예측하는데 매우 유용한 방법으로 활용될 수 있을 것이다. This study aims to analyze the effects of climatic and geographical factors based on the concept of ecological niche which is utilized extensively to predict the geographical distribution of biological species on the accuracy of species distribution models. The target species were non-native plants, which were found in subalpine zone of Odaesan National Park. And two critical variables, including climate and topological variables, were used for investigating the species distribution model analyzed by the Maxent algorithm. The climate variables included temperature and precipitation, and altitude above the sea level, slope, topographic wetness index, and streamflow were used as geographical variables. the effects on the species distribution by those variables will be examined. The result of application of the species distribution model which Maximum entropy, Maxent, algorithm utilized extensively and verified in recent ecology field is applied with was assessed. How much the actual investigated area was included in the predicted area distributed with the foreign plants was used for the examining process by the accuracy level with the value of AUC of ROC (Area Under Curve of Receiver Operating Characteristic) and by comparing the possible maximum composition rate of non-native species depending on the models.). Rather than considering either of biological climatic variables or geographical variables only, the accuracy level of the model applying both of them at the same time turned out to be the highest among the 3 models even though there was no significant difference among the models with the AUC value, 0.997 as well as the model showed the highest possible maximum composition rate, 99.5%, of the non-native species. In addition, with the setting of the potential distribution area of foreign plants with more than 50% of the possible composition rate of non-native species, the result of comparing the area showed the smallest distribution area which was predicted with the sized of 4,174 ㎢ considering the climatic and geographical variables. This result indicated that the analysis result is rather stable not being sensitive to the types and numbers of variables which explains the prediction result of the models and indirectly suggested that the distribution of non-native plants reflects the complexity of climatic and geographical features rather than environmental characteristics simply. In conclusion, the model that applied Maxent algorithm to various environmental variables may be very useful to predict the potential distribution area of various biological species in the National Park.

대리변수를 이용한 한반도 수질 및 수생태계 부문의 기후변화 취약성 평가

이건행 ( Keon Haeng Lee ),정유진 ( Eu Gene Chung ),김경현 ( Kyung Hyun Kim ),유정아 ( Jeong Ah Yu ),이은정 ( Eun Jeong Lee ) 한국물환경학회 2012 한국물환경학회지 Vol.28 No.3

This study aims at assessing vulnerability of water quality and aquatic ecosystem to climate change by using proxy variables. Vulnerability to climate change is defined as a function of exposure to climate, sensitivity, and adaptive capacity. Detailed proxy variables were selected considering availability and then standardized by re-scaling concept. After adequate weights were assigned to standardized proxy variables by Delphi technique, vulnerability index was calculated. As results, vulnerability of adjacent regions to coastal areas include water quality and aquatic ecosystem is relatively higher than that of inland areas, and especially adjacent region to the western and southeast seas, and Jeju show high vulnerabilities. Vulnerability in the future was performed based on A1B scenario (IPCC, 2000). Temporally, the increase of vulnerability from 2050s to 2100s may be larger than the increase from 2000s to 2050s. Because vulnerability index was estimated through the relationship among various proxy variables, it is important to consider characteristics of local region with measurements and policies for reduction of sensitivity and enhancement of adaptive capacity on climate change. This study is expected to be useful in planning adaptation measures and selecting priority to the policy on climate change.

The Impacts of Climate Variability on Household Consumption: Evidence Based on Village Weather Data in Indonesia

Pratiwi Ira Eka,박복영 대외경제정책연구원 2023 East Asian Economic Review Vol.27 No.4

This study investigates the impacts of long-term climate variability on household consumption in Indonesia, a country highly vulnerable to climate change. The analysis combines household survey data from nearly 5,998 families with satellite-derived weather data from NASA POWER spanning 30 years. We use the long-term variability in temperature and precipitation as a proxy for climate change. This study examines the impact of climate change which proceeds over the long term, unlike previous studies concerning one-off or short-term climate events. In addition, using satellite data enhances the accuracy of households’ exposure to climate variability. The analysis finds that households in a village with higher temperature and precipitation variability significantly consume less food. This implies that households more exposed to climate change are at higher risk of malnutrition in developing countries. This study has a limitation that it cannot rule out the potential endogeneity of choosing a climate vulnerable residential location due to economic poorness.

REVIEW Changes in Weather and Climate Extremes over Korea and Possible Causes: A Review

Seung-Ki Min,Seok-Woo Son,Kyong-Hwan Seo,Jong-Seong Kug,Soon-Il An,최용상,정지훈,김백민,Ji-Won Kim,Yeon-Hee Kim,이준이,Myong-In Lee 한국기상학회 2015 Asia-Pacific Journal of Atmospheric Sciences Vol.51 No.2

Weather and climate extremes exert devastating influence on human society and ecosystem around the world. Recent observations show increase in frequency and intensity of climate extremes around the world including East Asia. In order to assess current status of the observed changes in weather and climate extremes and discuss possible mechanisms, this study provides an overview of recent analyses on such extremes over Korea and East Asia. It is found that the temperature extremes over the Korean Peninsula exhibit long-term warming trends with more frequent hot events and less frequent cold events, along with sizeable interannual and decadal variabilities. The comprehensive review on the previous literature further suggests that the weather and climate extremes over East Asia can be affected by several climate factors of external and internal origins. It has been assessed that greenhouse warming leads to increase in warm extremes and decrease in cold extremes over East Asia, but recent Arctic sea-ice melting and associated warming tends to bring cold snaps to East Asia during winter. Internal climate variability such as tropical intraseasonal oscillation and El NiñoSouthern Oscillation can also exert considerable impacts on weather and climate extremes over Korea and East Asia. It is, however, noted that our current understanding is far behind to estimate the effect of these climate factors on local weather and climate extremes in a quantitative sense.

Sensitivity of FAO-Penman-Monteith Reference Evapotranspiration to Climate Variables

( Ahmad Mirza Junaid ),( Kyung Sook Choi ) 한국농공학회 2016 한국농공학회 학술대회초록집 Vol.2016 No.-

Sensitivity analysis of reference evapotranspiration (ET_o) is essential to determine the expected fluctuations of ET_o in response to a known change in a specific climate variable. This study analyzed the sensitivity of ET_o to maximum temperature (T_max), minimum temperature (T_min), relative humidity (RH), wind speed (u₂), and sunshine hours (n) for command area of Upper Chenab Canal in Punjab, Pakistan. FAO-Penman-Monteith (FAO-PM) equation was used to estimate ET_o by using a weather data set of 32-years from 1980-2012. Long term average value of each climate variable was varied with in a possible range of -20% to +20% with an interval of 5% and resulting ET_o variations were plotted as sensitivity curves. ET_o showed maximum response to change in T_max followed by n, T_min, u₂ and RH. Dimension less sensitivity coefficients were also derived for each climate variable to mathematically define the sensitivity of ET_o. Sensitivity coefficients of n and T_max were highest showing that their influence on ET_o variations would be maximum. Sensitivity coefficients of RH were negative showing that ET_o would decrease as RH increase and vice versa. In general, ET_o showed more sensitivity to climate variability in summer season. The influence of T_max, n and T_min was higher during summer months whereas influence of u2 and RH was higher during winter months. Results suggests that in context of latest warming trends caused by global warming, atmospheric evaporative demands of study area could rise drastically which would be a challenging situation for future agricultural water management.

재배 시기별 기후변수가 논벼의 단위면적당 생산성과 변동성에 미치는 영향 분석

조현경 ( Hyun Kyong Cho ),권오상 ( Oh Sang Kwon ) 한국농업경제학회 2014 農業經濟硏究 Vol.55 No.3

This study examines the impacts of seasonal climate variables such as monthly mean temperature, accumulated precipitation, sunshine duration and daily range of temperature on rice yield levels and variability in Kore. AJust-Pope function is applied to a panel data set of 59 cities and towns with the corresponding climate data. Future rice productivity and variability are forecasted based on the estimation results under two different RCP scenarios. It is found that climate variables affect both productivity and variability of rice production although there are seasonal differences in their direction of influence. Productivity is affected by sunshine duration and daily range in the grain-filling months as well as temperature and precipitation. Higher temperature in the vegetative phase reduces yield variability while higher precipitation in the grain-filling season increases output risk. It is shown that there is a trade-off between future productivity and variability, depending on the RCP scenarios, due to the countervailing effects of climate variables.

13세기 중국 지역의 기후변동과 기근

김대기,정주영,이찬수,윤은숙 한국생태환경사학회 2023 생태환경과역사 Vol.- No.11

중국역사에서 10세기~13세기는 ‘송・원 온난기’로 이해할 수 있다. 대용자료(proxy-data)를 근거로 한 자연과학적 연구결과에 따르면, 13세기 온난기 동안 기후는 대체로 온난습윤했다. 문헌기록 상으로 볼 때, 12세기는 분명 한랭기였던 것으로 보인다. 13세기로 접어들면서 이상 온난 기후 기록이 눈에 띄게 증가하고 있다. 회수 이남지역(A지역)과 특히 D지역(장소 특정이 어려운 기사)에서 그러하다. 회수・진령산맥 이북지역~장성 이남 지역(B지역)은 11세기~13세기 동안 이상 한랭기후가 꾸준히 등장한다. 이 지역은 간헐적 혹한이 존재했을 가능성이 있다. 13세기 후반기에 대체로 장성 이북지역(C지역) 등 북쪽지역에서 한랭화가 조금 더 강하게 나타나고 회수 이남에서는 약한 것으로 보아 본격적인 한랭기로 접어들었다기보다는 온난기에서 한랭기로 넘어가는 전환기로 해석할 수 있겠다. 태평양 여름몬순의 영향을 많이 받는 중국은 지난 1800년 동안 대체로 온난기에는 습윤했고 한랭기에는 건조한 기후 패턴을 보였다. 문헌기록 상으로도 한랭기였던 12세기 중반 이후 특히, 1180년대~1190년대에 기근이 폭증했다. 그러다가 온난기가 진행된 13세기에 들어서면서 기근이 현저히 감소하였으나, 1260년대부터 화북지역에서 기근이 급격히 증가하고 뒤를 따라 회수 이남 지역에서도 기근이 급격히 증가하는 추세를 보인다. 13세기 전반기의 온난습윤한 기후는 몽골이 서정(西征)을 진행하는 데 유리한 조건을 제공했다. 그리고 1260년대 후반 이후 기온이 하강하면서 찾아온 초원지역의 조드(Jud) 현상과 화북 지방의 기근 증가는 쿠빌라이에게 더 많은 영지와 잉여생산물의 확보를 위한 정치・군사적 행동을 추동하는 여러 요인 중 하나가 되었을 것이다. In history of China, the period between the tenth and thirteenth century is understood as the ‘warm period.’ Based on a research in the field of natural science, which utilized the proxy-data methodology, the climate during the ‘warm period’ of the thirteenth century was mostly warm-humid. Available textual evidence suggests that the twelfth century was indeed in the cold climate. Abnormal temperature appeared more frequently at the thresh hold of the thirteenth century. This trend is more apparent in Area A (South of Huai Shui) and Area D (Unidentifiable region based on available historical evidence). Frequent presence of cold climate is also observed in Area B (Qinling Mountains and the Huabei-South of the Great Wall) between the eleventh and thirteen century. It is possible that intermittent extreme cold climate was present in this area. Evidently the late thirteenth century can be identified as a transitional period, for then cold climate appeared more strongly in the northern area such as Area C (North of the Great Wall) whereas that in the the South of Huai Shui was weaker. China is under heavy influence of Summer Monsoon of the Pacific, and as a result, in the past 1,800 years, it experienced humid climate during the warm period and dry climate during the cold period. As shown in textual evidence which has this time as the cold period, famine happened much more frequently after the mid-twelfth century and especially between 1180s and 1190s. Famine drastically weakened in the thirteenth century as the warm period began; however, starting from the 1260s, famine broke out more rapidly first in the Huabei area and then in the South of Huai Shui. The warm-humid climate of the early thirteenth-century favored the Mongol’s western campaign with better odds. Drop of temperature after the late 1260s brought the Jud phenomenon in the grasslands and increased the frequency of famine. These factors must have been one of many motivations that influenced Kublai to pursue more political and military actions to obtain more lands and surplus goods.

A Linear Projection for the Timing of Unprecedented Climate in Korea

신호정,장찬주,정일웅 한국기상학회 2017 Asia-Pacific Journal of Atmospheric Sciences Vol.53 No.4

Recently we have had abnormal weather events worldwide that are attributed by climate scientists to the global warming induced by human activities. If the global warming continues in the future and such events occur more frequently and someday become normal, we will have an unprecedented climate. This study intends to answer when we will have an unprecedented warm climate, focusing more on the regional characteristics of the timing of unprecedented climate. Using an in-situ observational data from weather stations of annual-mean surface air temperature in Korea from 1973 to 2015, we estimate a timing of unprecedented climate with a linear regression method. Based on the in-situ data with statistically significant warming trends at 95% confidence level, an unprecedented climate in Korea is projected to occur first in Cheongju by 2043 and last in Haenam by 2168. This 125-year gap in the timing indicates that a regional difference in timing of unprecedented climate is considerably large in Korea. Despite the high sensitivity of linear estimation to the data period and resolution, our findings on the large regional difference in timing of unprecedented climate can give an insight into making policies for climate change mitigation and adaptation, not only for the central government but for provincial governments.