High-quality reconstruction of China’s natural streamflow

Miao, Chiyuan; Gou, Jiaojiao; Fu, Bojie; Tang, Qiuhong; Duan, Qingyun; Chen, Zhongsheng; Lei, Huimin; Chen, Jie; Guo, Jiali; Borthwick, Alistair G. L.; Ding, Wenfeng; Duan, Xingwu; Li, Yungang; Kong, Dongxian; Xiao-ying, Guo; Wu, Jingwen

doi:10.1016/j.scib.2021.09.022

Cited by 61 publications

(21 citation statements)

References 54 publications

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“…It should be noted that the model errors of Noah‐MP quantified in this study can be significantly reduced by parameter optimization. For example, calibrating the soil parameters can largely improve the RF simulations (Gou et al., 2021; Miao et al., 2021), and calibrating the maximum carboxylation rate and specific leaf area can effectively improve the GPP simulations (Li, Duan, et al., 2018).…”

Section: Discussionmentioning

confidence: 99%

Global Evaluation of the Noah‐MP Land Surface Model and Suggestions for Selecting Parameterization Schemes

Miao

Guo

et al. 2022

JGR Atmospheres

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This study examines the overall performance of the Noah with multiparameterization (Noah‐MP) land surface model in simulating key land‐atmosphere variables at a global scale and explores the feasibility of running Noah‐MP with regionally different combinations of parameterization schemes. We conducted Noah‐MP ensemble simulations and evaluated the annual means and seasonal cycles of the simulated latent heat flux, net radiation (RN), runoff, soil moisture, snow water equivalent, land surface temperature (LST), leaf area index (LAI), and gross primary productivity (GPP) against a wide variety of global products. The results show that the global patterns of the modeled annual means of these variables generally agree with those of the reference data sets. By evaluating the best simulations in the ensemble, we show that Noah‐MP performs very well in simulating global LST and RN but produces biases in annual mean LAI and GPP by more than 40% in most herbaceous regions. Overall, the main disagreements between Noah‐MP and the reference data sets occurred in the tropical, polar, high‐altitude, and hyperarid regions. This study also highlights the potential of land‐cover‐specific combinations of parameterization schemes to produce optimal modeling results over different land‐cover types. In addition, we strongly suggest the use of multi‐objective optimization of the key parameterizations and parameters to further improve the Noah‐MP's overall performance.

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Section: Discussionmentioning

confidence: 99%

Global Evaluation of the Noah‐MP Land Surface Model and Suggestions for Selecting Parameterization Schemes

Miao

Guo

et al. 2022

JGR Atmospheres

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“…(2021), looking at the Loess Plateau (LP; the core region implementing the GGP), declared that climate conditions—especially precipitation—can greatly affect vegetation growth over this region. Furthermore, for alpine ecosystems such as the Tibetan Plateau (TP), vegetation conditions are strongly affected by precipitation and temperature changes (Miao et al., 2022; Q. Wang et al., 2014). Rapidly increased vegetation cover in China has led to large variability in E , especially in arid and semiarid areas (such as in northwestern China).…”

Section: Introductionmentioning

confidence: 99%

Effects of Vegetation Changes and Multiple Environmental Factors on Evapotranspiration Across China Over the Past 34 Years

Zheng

Miao

et al. 2022

Earth's Future

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Documenting the spatiotemporal changes in vegetation cover and hydrological cycle of the Earth system and understanding how they interact are important especially under climate warming. In this research, we quantified the changes in vegetation and evapotranspiration (E) across China during 1982–2015 and then revealed the complex relationships in climate–vegetation–evapotranspiration system. Results show that the upward trend in vegetation leaf area index (LAI) during 2000–2015 (an increase of 0.95% per year) was almost 8 times the trend during 1982–1999. The zones of the Loess Plateau and the Three‐North Shelter Forest Program are the most notable areas for LAI increases between these two periods, with increases of 11.65% and 2.87%, respectively. Increased LAI, along with the warming climate, has accelerated E across China in the past several decades, and the annual increase in the E rate was 0.34% (1.34 mm year−1) during 1982–1999 and 0.40% (1.62 mm year−1) during 2000–2015. The zones of the Loess Plateau and the karst landform are the most notable areas for transpiration increases, with individual increases of 10% and 5%, respectively. In general, the dominant causes for evaporation changes across all of China are temperature and precipitation, while the main reasons for transpiration changes include temperature, LAI, and sunshine duration. This study improves our understanding of the relationships within the climate–vegetation–evapotranspiration system and provides important support for future ecological policies across China.

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“…Furthermore, the projected warming of some areas of the PTP region will exceed 4 °C above pre-industrial levels by 2100, which far exceeds the 2 °C goal set by the Paris Agreement of the United Nations Framework Convention on Climate Change (Yao et al 2017). The warming in the PTP region is causing Earth system changes characterized by intensive interactions among the processes of the atmosphere, hydrosphere, cryosphere, and biosphere, and is resulting in environmental threats such as glacier retreat, ice collapse, glacial lake expansion, and frequent glacier lake outburst flood (Miao et al 2021;Yang et al 2014;Yao et al 2019). These changes may have impacts on the regional and global hydrologic cycle, thereby hindering socioeconomic development in countries along the routes of the Belt and Road Initiative.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of historical CMIP6 model simulations and future projections of temperature over the Pan-Third Pole region

Fan

Duan

Shen

et al. 2021

Environ Sci Pollut Res

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The Pan-Third Pole (PTP) region, which encompasses the Eurasian highlands and their surroundings, has experienced unprecedented, accelerated warming during the past decades. This study evaluates the performance of historical simulation runs of the Coupled Model Intercomparison Project (CMIP6) in capturing spatial patterns and temporal variations observed over the PTP region for mean and extreme temperatures. In addition, projected changes in temperatures under four Shared Socioeconomic Pathway (SSP) scenarios (SSP1‐2.6, SSP2‐4.5, SSP3-7.0, and SSP5‐8.5) are also reported. Four indices were used to characterize changes in temperature extremes: the annual maximum value of daily maximum temperature (TXx), the annual minimum value of daily minimum temperature (TNn), and indices for the percentage of warm days (TX90p) and warm nights (TN90p). Results indicate that most CMIP6 models generally capture the characteristics of the observed mean and extreme temperatures over the PTP region, but there still are slight cold biases in the Tibetan Plateau. Future changes of mean and extreme temperatures demonstrate that a strong increase will occur for the entire PTP region during the twenty-first century under all four SSP scenarios. Between 2015 and 2099, ensemble area-averaged annual mean temperatures are projected to increase by 1.24 °C/100 year, 3.28 °C/100 year, 5.57 °C/100 year, and 7.40 °C/100 year for the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, respectively. For TXx and TNn, the most intense warming is projected in Central Asia. The greatest number of projected TX90p and TN90p will occur in the Southeast Asia and Tibetan Plateau, respectively.

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High-quality reconstruction of China’s natural streamflow

Cited by 61 publications

References 54 publications

Global Evaluation of the Noah‐MP Land Surface Model and Suggestions for Selecting Parameterization Schemes

Global Evaluation of the Noah‐MP Land Surface Model and Suggestions for Selecting Parameterization Schemes

Effects of Vegetation Changes and Multiple Environmental Factors on Evapotranspiration Across China Over the Past 34 Years

Evaluation of historical CMIP6 model simulations and future projections of temperature over the Pan-Third Pole region

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