Insight from CMIP6 SSP-RCP scenarios for future drought characteristics in China

Su, Buda; Huang, Jinlong; Mondal, Sanjit Kumar; Zhai, Jun; Wang, Yanjun; Wen, Shanshan; Gao, Miaoni; Lv, Yanran; Jiang, Shan; Jiang, Tong; Li, Aiwei

doi:10.1016/j.atmosres.2020.105375

Cited by 238 publications

(125 citation statements)

References 74 publications

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“…The study found that there were more drought episodes under the moderate and severe conditions at the coast of the country in the south, while at the northern parts, there were persistent droughts of higher severity. Many other studies have also reported drought occurrences in the country [36][37][38]. Similar findings have been reported from North Korea [56][57][58], Japan [58], and China [59,60] that neighbor South Korea.…”

Section: Future Droughtsupporting

confidence: 81%

“…The SWAT model can perform runoff analysis of the watershed using relatively simple input data. In previous studies [36][37][38], meteorological drought indices such as SPI, SPEI, and potential evaporation were analyzed, but this study used a hydrological drought index. Thus, three drought indices, namely, SPI, SPEI, and SDI, were calculated for 3-, 6-, 9-, and 12-month durations.…”

Section: Discussionmentioning

confidence: 99%

“…Jiang et al [32] found that models have improved from Coupled Model Intercomparison Project 5 (CMIP5) to CMIP6 for climatological temperature and precipitation and winter monsoon but display little improvement for the interannual temperature and precipitation variability and summer monsoon in East Asia monsoon. Therefore, the comparative studies between Coupled Model Intercomparison Project 5 (CMIP5) and CMIP6 have been conducted all over the world in terms of spatial distributions [33], uncertainty analysis [34], future projections [35], and drought characteristics of India [36] and China [37,38].…”

Section: Introductionmentioning

confidence: 99%

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Comparison of Projection in Meteorological and Hydrological Droughts in the Cheongmicheon Watershed for RCP4.5 and SSP2-4.5

et al. 2021

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Due to the recent appearance of shares socioeconomic pathway (SSP) scenarios, there have been many studies that compare the results between Coupled Model Intercomparison Project (CMIP)5 and CMIP6 general circulation models (GCMs). This study attempted to project future drought characteristics in the Cheongmicheon watershed using SSP2-4.5 of Australian Community Climate and Earth System Simulator-coupled model (ACCESS-CM2) in addition to Representative Concentration Pathway (RCP) 4.5 of ACCESS 1-3 of the same institute. The historical precipitation and temperature data of ACCESS-CM2 were generated better than those of ACCESS 1-3. Two meteorological drought indices, namely, Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were used to project meteorological drought while a hydrological drought index, Standardized Streamflow Index (SDI), was used to project the hydrological drought characteristics. The metrological data of GCMs were bias-corrected using quantile mapping method and the streamflow was obtained using Soil and Water Assessment Tool (SWAT) and bias-corrected meteorological data. As a result, there were large differences of drought occurrences and severities between RCP4.5 and SSP2-4.5 for the values of SPI, SPEI, and SDI. The differences in the minimum values of drought index between near (2021–2060) and far futures (2061–2100) were very small in SSP2-4.5, while those in RCP4.5 were very large. In addition, the longest drought period from SDI was the largest because the variation in precipitation usually affects the streamflow with a lag. Therefore, it was concluded that it is important to consider both CMIP5 and CMIP6 GCMs in establishing the drought countermeasures for the future period.

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Section: Future Droughtsupporting

confidence: 81%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Comparison of Projection in Meteorological and Hydrological Droughts in the Cheongmicheon Watershed for RCP4.5 and SSP2-4.5

et al. 2021

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“…However, partly due to the differences in the regions of interest and data availability, it is rather difficult to compare the performances of different models in detail. Su et al (2021) shows that for the humid and semi-humid regions in China, including PRB, r values between simulated and observed drought characteristics during 1986-2005 are generally smaller than 0.3 according to the CMIP5 and CMIP6 models. Turco et al (2017) Du et al (2019) found that over the Southwestern United States, there is an overall moderate correlation (r values of 0.3-0.7) between surface wetness index and the Palmer moisture anomaly index in summer for the period of 2002-2017.…”

Section: Comparison With Other Approachesmentioning

confidence: 94%

Robust Meteorological Drought Prediction Using Antecedent SST Fluctuations and Machine Learning

Wang

et al. 2021

Water Resources Research

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While reliable drought prediction is fundamental for drought mitigation and water resources management, it is still a challenge to develop robust drought prediction models due to complex local hydro‐climatic conditions and various predictors. Sea surface temperature (SST) is considered as the fundamental predictor to develop drought prediction models. However, traditional models usually extract SST signals from one or several specific sea zones within a given time span, which limits full use of SST signals for drought prediction. Here, we introduce a new meteorological drought prediction approach by using the antecedent SST fluctuation pattern (ASFP) and machine learning techniques (e.g., support vector regression (SVR), random forest (RF), and extreme learning machine (ELM)). Three models (i.e., ASFP‐SVR, ASFP‐ELM, and ASFP‐RF) are developed for ensemble, probability, and deterministic drought predictions. The Colorado, Danube, Orange, and Pearl River basins with frequent droughts over different continents are selected, as the cases, where standardized precipitation evapotranspiration index (SPEI) are predicted at the 1° × 1° resolution with 1‐ and 3‐month lead times. Results show that the ASFP‐ELM model can effectively predict space‐time evolutions of drought events with satisfactory skills, outperforming the ASFP‐SVR and ASFP‐RF models. Our study has potential to provide a reliable tool for drought prediction, which further supports the development of drought early warning systems.

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“…The future variables were derived from the new climate scenarios proposed in the Sixth International Coupling Model Comparison Program (CMIP6), namely Shared Economic Paths (SSPs), which had a higher starting point for prediction than RCPs and can provide More diverse air pollution emission scenarios [41]. Among them, SSP1-2.6 and SSP5-8.5 described the lowest-emission sustainable development scenario and the highestemission conventional development scenario respectively, which were selected to drive the optimized MaxEnt model to predict the changes of glaciers in the future and provided more reasonable evaluation conditions for the study of the glacier future trends.…”

Section: Environmental Parametersmentioning

confidence: 99%

Simulation of the Potential Distribution of the Glacier Based on Maximum Entropy Model in the Tianshan Mountains, China

Wang

Zhang

Liu

et al. 2021

Water

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Under the background of global climate change, the variation in the spatial distribution and ice volume of mountain glaciers have a profound influence on regional economic development and ecological security. The development of glaciers is like biological succession; when climate change approaches or exceeds the threshold of suitable conditions for glacier development, it will lead to changes in potential distribution pattern. Therefore, from the perspective of the "biological" characteristics of glaciers, it is a beneficial exploration and attempt in the field of glaciology to explore its potential distribution law with the help of the niche model. The maximum entropy model (MaxEnt) can explain the environmental conditions suitable for the survival of things by analyzing the mathematical characteristics and distribution laws of samples in space. According to glacier samples and the geographical environment data screened by correlation analysis and iterative calculation, the potential distribution pattern of Tianshan glaciers in China in reference years (1970–2000) was simulated by MaxEnt. This paper describes the contribution of geographical environmental factors to distribution of glaciers in Tianshan Mountains, quantifies the threshold range of factors affecting the suitable habitat of glaciers, and predicts the area variation and distribution pattern of glaciers under different climate scenarios (SSP1-2.6, SSP5-8.5) in the future (2040–2060, 2080–2100). The results show that the MaxEnt model has good adaptability to simulate the distribution of glaciers. The spatial heterogeneity of potential distribution of glaciers is caused by the spatio-temporal differences of hydrothermal combination and topographic conditions. Among the environmental variables, precipitation during the wettest month, altitude, annual mean temperature, and temperature seasonality have more significant effects on the potential distribution of glaciers. There is significant spatial heterogeneity in the potential distribution of glaciers in different watersheds, altitudes, and aspects. From the forecast results of glacier in various climatic scenarios in the future, about 18.16–27.62% of the total reference year glacier area are in an alternating change of melting and accumulation, among which few glaciers are increasing, but this has not changed the overall retreat trend of glaciers in the study area. Under the low emission scenario, the glacier area of the Tianshan Mountains in China decreased by 18.18% and 23.73% respectively in the middle and end of the 21st century compared with the reference years and decreased by 20.04% and 27.63%, respectively, under the high emission scenario, which showed that the extent of glacier retreat is more intense under the high emission scenario. Our study offers momentous theoretical value and practical significance for enriching and expanding the theories and analytical methods of the glacier change.

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Insight from CMIP6 SSP-RCP scenarios for future drought characteristics in China

Cited by 238 publications

References 74 publications

Comparison of Projection in Meteorological and Hydrological Droughts in the Cheongmicheon Watershed for RCP4.5 and SSP2-4.5

Comparison of Projection in Meteorological and Hydrological Droughts in the Cheongmicheon Watershed for RCP4.5 and SSP2-4.5

Robust Meteorological Drought Prediction Using Antecedent SST Fluctuations and Machine Learning

Simulation of the Potential Distribution of the Glacier Based on Maximum Entropy Model in the Tianshan Mountains, China

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