• Title/Summary/Keyword: Quantile Mapping

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A selection of optimal method for bias-correction in Global Seasonal Forecast System version 5 (GloSea5) (전지구 계절예측시스템 GloSea5의 최적 편의보정기법 선정)

  • Son, Chanyoung;Song, Junghyun;Kim, Sejin;Cho, Younghyun
    • Journal of Korea Water Resources Association
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    • v.50 no.8
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    • pp.551-562
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    • 2017
  • In order to utilize 6-month precipitation forecasts (6 months at maximum) of Global Seasonal Forecast System version 5 (GloSea5), which is being provided by KMA (Korea Meteorological Administration) since 2014, for water resources management as well as other applications, it is needed to correct the forecast model's quantitative bias against observations. This study evaluated applicability of bias-correction skill in GloSea5 and selected an optimal method among 11 techniques that include probabilistic distribution type based, parametric, and non-parametric bias-correction to fix GloSea5's bias in precipitation forecasts. Non-parametric bias-correction provided the most similar results with observed data compared to other techniques in hindcast for the past events, yet relatively generated some discrepancies in forecast. On the contrary, parametric bias-correction produced the most reliable results in both hindcast and forecast periods. The results of this study are expected to be applicable to various applications using seasonal forecast model such as water resources operation and management, hydropower, agriculture, etc.

Assessing Future Water Demand for Irrigating Paddy Rice under Shared Socioeconomic Pathways (SSPs) Scenario Using the APEX-Paddy Model (APEX-paddy 모델을 활용한 SSPs 시나리오에 따른 논 필요수량 변동 평가)

  • Choi, Soon-Kun;Cho, Jaepil;Jeong, Jaehak;Kim, Min-Kyeong;Yeob, So-Jin;Jo, Sera;Owusu Danquah, Eric;Bang, Jeong Hwan
    • Journal of The Korean Society of Agricultural Engineers
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    • v.63 no.6
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    • pp.1-16
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    • 2021
  • Global warming due to climate change is expected to significantly affect the hydrological cycle of agriculture. Therefore, in order to predict the magnitude of climate impact on agricultural water resources in the future, it is necessary to estimate the water demand for irrigation as the climate change. This study aimed at evaluating the future changes in water demand for irrigation under two Shared Socioeconomic Pathways (SSPs) (SSP2-4.5 and SSP5-8.5) scenarios for paddy rice in Gimje, South Korea. The APEX-Paddy model developed for the simulation of paddy environment was used. The model was calibrated and validated using the H2O flux observation data by the eddy covariance system installed at the field. Sixteen General Circulation Models (GCMs) collected from the Climate Model Intercomparison Project phase 6 (CMIP6) and downscaled using Simple Quantile Mapping (SQM) were used. The future climate data obtained were subjected to APEX-Paddy model simulation to evaluate the future water demand for irrigation at the paddy field. Changes in water demand for irrigation were evaluated for Near-future-NF (2011-2040), Mid-future-MF (2041-2070), and Far-future-FF (2071-2100) by comparing with historical data (1981-2010). The result revealed that, water demand for irrigation would increase by 2.3%, 4.8%, and 7.5% for NF, MF and FF respectively under SSP2-4.5 as compared to the historical demand. Under SSP5-8.5, the water demand for irrigation will worsen by 1.6%, 5.7%, 9.7%, for NF, MF and FF respectively. The increasing water demand for irrigating paddy field into the future is due to increasing evapotranspiration resulting from rising daily mean temperatures and solar radiation under the changing climate.

SSP Climate Change Scenarios with 1km Resolution Over Korean Peninsula for Agricultural Uses (농업분야 활용을 위한 한반도 1km 격자형 SSP 기후변화 시나리오)

  • Jina Hur;Jae-Pil Cho;Sera Jo;Kyo-Moon Shim;Yong-Seok Kim;Min-Gu Kang;Chan-Sung Oh;Seung-Beom Seo;Eung-Sup Kim
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.26 no.1
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    • pp.1-30
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    • 2024
  • The international community adopts the SSP (Shared Socioeconomic Pathways) scenario as a new greenhouse gas emission pathway. As part of efforts to reflect these international trends and support for climate change adaptation measure in the agricultural sector, the National Institute of Agricultural Sciences (NAS) produced high-resolution (1 km) climate change scenarios for the Korean Peninsula based on SSP scenarios, certified as a "National Climate Change Standard Scenario" in 2022. This paper introduces SSP climate change scenario of the NAS and shows the results of the climate change projections. In order to produce future climate change scenarios, global climate data produced from 18 GCM models participating in CMIP6 were collected for the past (1985-2014) and future (2015-2100) periods, and were statistically downscaled for the Korean Peninsula using the digital climate maps with 1km resolution and the SQM method. In the end of the 21st century (2071-2100), the average annual maximum/minimum temperature of the Korean Peninsula is projected to increase by 2.6~6.1℃/2.5~6.3℃ and annual precipitation by 21.5~38.7% depending on scenarios. The increases in temperature and precipitation under the low-carbon scenario were smaller than those under high-carbon scenario. It is projected that the average wind speed and solar radiation over the analysis region will not change significantly in the end of the 21st century compared to the present. This data is expected to contribute to understanding future uncertainties due to climate change and contributing to rational decision-making for climate change adaptation.