Quantification of model uncertainty in sub-daily extreme precipitation projections

Majhi, Archana; Dhanya, C. T.; Chakma, Sumedha

doi:10.1016/j.gloplacha.2022.103967

Cited by 5 publications

(3 citation statements)

References 92 publications

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“…The number of consistent projected results can affect the credibility of the conclusions [27]. Therefore, this study examines the similarity of climate simulation results and explores the similarity of simulated temperature and precipitation between models [28]. The specific steps are referenced in the literature [29,30].…”

Section: Similarity Test Of Climate Model Simulation Resultsmentioning

confidence: 99%

Evaluation and Projection of Climate Change in the Second Songhua River Basin Using CMIP6 Model Simulations

Xiao,

Zhuo,

Sun

et al. 2023

Atmosphere

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The aim of this study is to evaluate the performance of the Global Climate Model (GCM) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) in historical simulations of temperature and precipitation. The goal is to select the best performing GCMs for future projection of temperature and precipitation in the Second Songhua River Basin under multiple shared socioeconomic pathways (SSPs). Interannual variability skill (IVS) and Taylor diagrams are used to evaluate the spatiotemporal performance of GCMs against temperature and precipitation data published by the China Meteorological Science Commons during 1956–2016. In addition, five relatively independent models are selected to simulate the temperature and precipitation for 2021–2050 using Hierarchical Clustering. The selected models are CMCC-ESM2, EC-Earth3-Veg-LR, IPSL-CM6A-LR, MIROC-ES2L, and MPI-ESM1-2-HR. The projected results find that SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios show an increasing trend of future annual mean temperature and precipitation. However, for annual precipitation, there is a mixed state of increase and decrease among different models on the seasonal scale. In general, future temperature and precipitation changes still show a trend of growth and uneven distribution in the Second Songhua River Basin, which may be further accelerated by human activities.

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Section: Similarity Test Of Climate Model Simulation Resultsmentioning

confidence: 99%

Evaluation and Projection of Climate Change in the Second Songhua River Basin Using CMIP6 Model Simulations

Xiao,

Zhuo,

Sun

et al. 2023

Atmosphere

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“…The weighted variance approach resulted reduced uncertainty as compared to the unweighted variance approach (See Figure S2). Additionally, by utilizing this methodology, uncertainty in quantified in the projections of sub-daily precipitation extremes [31] .…”

Section: Weighted Variance Approach For Uncertainty Estimationmentioning

confidence: 99%

Mutual information based weighted variance approach for uncertainty quantification of climate projections

2023

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“…Moreover, even though many studies have investigated the changes in daily and monthly precipitation (Almazroui & Saeed, 2020; Menon et al, 2013; Scoccimarro et al, 2015), the study for subdaily precipitation extremes is very limited due to the lack of observed time series (Hosseinzadehtalaei et al, 2020; Morrison et al, 2019). However, existing results have indicated that subdaily precipitation records can better capture intermittent characteristics and minor variations of precipitation extremes compared with daily precipitation (Förster & Thiele, 2020; Majhi et al, 2022). Hence, exploring the evolution of subdaily precipitation extremes is important.…”

Section: Introductionmentioning

confidence: 99%

Long‐term evolution and non‐stationary behaviours of daily and subdaily precipitation extremes in China

Liu,

Chen,

Xiong

et al. 2024

Intl Journal of Climatology

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The rise of extreme precipitation events has attracted wide attention throughout the world. However, the analysis of precipitation extremes is not sufficient in the short period of instrumental observation and it is complicated by their non‐stationary behaviours. As a period dominated by natural forcing, the last millennium is helpful for understanding long‐term changes in precipitation extremes. Therefore, this study aimed to (1) investigate changes in daily and subdaily precipitation extremes in China from the last millennium to the end of the twenty‐first century, (2) detect the non‐stationarity of precipitation extremes and (3) compare design storms by using stationary and non‐stationary distributions. The annual maximum 1‐day precipitation (RX1day) and annual maximum 3‐hour precipitation (RX3hour) are used to quantify variations of precipitation extremes. The results show that the trend of RX1day was insignificant for the Medieval Climate Anomaly (MCA, 950–1250) and the Little Ice Age (LIA, 1500–1800). For the historical period (1850–2014), the trend of RX1day and RX3hour was insignificant in most subregions. In addition, the differences for RX1day between the historical period and the MCA/LIA were mostly in the range of −5% to 5%. For the future period (2015–2100), RX1day and RX3hour are projected to increase in almost all land grids compared with the historical period, and they show greater increases in western China than eastern China. The non‐stationarity of RX1day and RX3hour is mainly found under the high‐emission scenario. Moreover, stationary generalized extreme value (GEV) distribution underestimates 50‐year return levels for RX1day and RX3hour in most areas compared with non‐stationary GEV distribution under the high‐emission scenario. Overall, this study suggests that daily and subdaily extreme precipitation will intensify over China in the future. For design storms, non‐stationary methods need to be used for risk management and engineering design under the high‐emission scenario.

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Quantification of model uncertainty in sub-daily extreme precipitation projections

Cited by 5 publications

References 92 publications

Evaluation and Projection of Climate Change in the Second Songhua River Basin Using CMIP6 Model Simulations

Evaluation and Projection of Climate Change in the Second Songhua River Basin Using CMIP6 Model Simulations

Mutual information based weighted variance approach for uncertainty quantification of climate projections

Long‐term evolution and non‐stationary behaviours of daily and subdaily precipitation extremes in China

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