연구보고서
- 저자
- 이우섭 박사
- 작성일
- 2016.03.14
- 조회
- 265
- 요약
- 목차
As the global climate changes, heat waves are likely to become more common, further increasing the need for preparedness and early warning systems. In order to provide early information about the probability of the heat wave occurrence from short-term to seasonal time scale, we evaluated the probability of heat waves using multi-time scale data.
First, this study investigated the interannual variation of heat wave frequency (HWF) in South Korea during the past 42 years (1973-2014) and examined its connection with large-scale atmospheric circulation changes. The regression of the leading principal component (PC) time series of HWF with large-scale atmospheric circulation identified a north-south dipole pattern between the South China Sea and Northeast Asia. When this large-scale circulation mode facilitates deep convection in South China Sea, it tends to weaken moisture transport from the South China Sea to Northeast Asia. Enhanced deep convection in the South China Sea triggers a source of Rossby wave train along southerly wind that generates positive geopotential height anomalies around Korea.
Regarding the occurrence of Korean heat waves, two major centers of interannual variability were identified in the regression pattern of the upper-level vorticity. We designate the vorticity difference at 150 hPa level between the average over 25~30 °N, 110~130 °E and the average over 35~45 °N, 120~140 °E as a favorable condition of Korean heat waves. The correlation between PC1 and the time series of vorticity difference reached up to 0.81 with significance at the 95 % confidence level by the Student’s t-test. As a result, we have made an effort to define new indices to assist in real-time monitoring, medium-range forecasting of the heat waves in Korean.
Second, we also assessed the predictability and probability of heat wave occurrence over Korea by applying the Observing System Research and Predictability Experiment Interactive Grand Global Ensemble (TIGGE) data for the Korean Heat wave Index (KHI) associated with large scale circulation. Based on the TIGGE datasets, KHI showed higher predictability of heat waves than those of maximum temperature (TMAX) and Bias corrected TMAX. The verification of Percent Correct and Threat Score and Equitable Threat Score(ETS) showed that the heat wave forecast using KHI compared to others regardless of forecast lead time was successfully carried out. KHI is able to provide an early warning forecast for heatwaves with 5 days up to 9 days forecast lead time (Figure 1). It can be reliable information for decision makers to provide efficacious and timely actions to prepare for imminent heatwaves. The timing and duration of heatwaves are important factors in terms of forecasting heatwaves because they have been shown to have an impact on health and well-being. It is appropriate to determine the starting time and ending time of a heatwave in Korea using KHI. Therefore, KHI will aid in monitoring and making reasonable determinations about heatwave occurrence in routine operations.
Third, we assessed prediction skill for forecasting heat wave in association with large scale patterns (GPH, OLR, T2M) out to 2-3 weeks lead time using pattern correlation skill score. Overall, the 500hPa GPH anomalies is well forecasted in GloSea5 at lead times of 2-3 weeks. GloSea5 was able to predict GPH and OLR anomalies similar to those observed over East Asia at lead time of 2-3 weeks for 2014 heat waves. Heat waves forecasts over longer lead times can become highly valuable resources for disaster risk reduction and adaptation planning.
Finally, we proposed a heat wave early warning system with response plan in order to reduce the damage caused by heat wave. Heat wave early warning systems involve forecasting of the heat wave occurrence, timely responses plans that target vulnerable populations, and evaluation of systems. Heat wave early warning systems will help improve public-health responses to severe heat waves.