Abstract
Serving as ‘the water tower of Asia’, the Tibetan Plateau (TP) supplies water resources to more than 1.4 billion people. It is warming more rapidly than the global average over the past ...decades, affecting regional hydrological cycle and ecosystem services. However, the anthropogenic (ANT) influence remains unknown. Here we assessed the human contribution to the observed TP warming based on coupled climate simulations and an optimal fingerprinting detection and attribution analysis. We show that the observed rapid warming on the TP (1.23 °C over 1961–2005) is attributable to human influence, and particularly, to the greenhouse gases with a contribution of 1.37 °C by the best estimate, which was slightly offset by anthropogenic aerosols. As the multi-model ensemble tends to underestimate the ANT warming trend, the constraint from the attribution results suggests an even warmer future on the TP than previously expected, implying further increased geohazard risks in the Asian water tower.
The Paris Agreement set a goal to keep global warming well below 2 °C and pursue efforts to limit it to 1.5 °C. Understanding how 0.5 °C less warming reduces impacts and risks is key for climate ...policies. Here, we show that both areal and population exposures to dangerous extreme precipitation events (e.g., once in 10- and 20-year events) would increase consistently with warming in the populous global land monsoon regions based on Coupled Model Intercomparison Project Phase 5 multimodel projections. The 0.5 °C less warming would reduce areal and population exposures to once-in-20-year extreme precipitation events by 25% (18-41%) and 36% (22-46%), respectively. The avoided impacts are more remarkable for more intense extremes. Among the monsoon subregions, South Africa is the most impacted, followed by South Asia and East Asia. Our results improve the understanding of future vulnerability to, and risk of, climate extremes, which is paramount for mitigation and adaptation activities for the global monsoon region where nearly two-thirds of the world's population lives.
The Tibetan Plateau (TP) plays an essential role in the global hydrological cycle. Unlike the well‐recognized surface warming, changes in precipitation over the TP and the underlying mechanisms ...remain ambiguous. A significant increase in the amount of precipitation over the southeastern TP in May over 1979–2014 (13.46% decade−1 of the climatology) is identified in this study, based on homogenized daily rain gauge data. Both the increased precipitation frequency and intensity have contributions. The coherent increases in soil moisture content and vegetation activities further confirm the precipitation trend, indicating a wetting and greening TP in the early summer in recent decades. The moisture budget analysis shows that this wetting trend in the past four decades is dominated by the increased water vapor convergence due to circulation changes, while increases in specific humidity play a minor role. The wetting trend over the TP in May results directly from the earlier onset of the South Asian summer monsoon (ASM) since the late 1970s associated with the phase transition of Interdecadal Pacific Oscillation around the late 1990s. The earlier onset of the ASM triggers low‐level southwesterly anomalies over the northern Indian Ocean, promoting moisture convergence and increased precipitation over the TP in May. Specifically, the increased amount of precipitation after the onset of the ASM explains 95% of the increase in the total amount of precipitation in May.
Plain Language Summary
The amount of precipitation in May over the Tibetan Plateau (TP) has increased significantly since 1979. Both the increased precipitation frequency and intensity have contributions. The coherent increases in soil moisture content and vegetation activities further confirm the precipitation trend, indicating a wetting and greening TP in the early summer in recent decades. The moisture budget analysis shows that this wetting trend in the past four decades is dominated by the increased water vapor convergence due to circulation changes, while increases in specific humidity play a minor role. The wetting trend over the TP in May results directly from the earlier onset of the South Asian summer monsoon since the late 1970s, which is fundamentally triggered by the interdecadal variability of the Pacific Ocean.
Key Points
The amount, frequency, and intensity of precipitation in May over the Tibetan Plateau have increased significantly since 1979
Soil moisture content and vegetation activities in the early summer increased as a response to the wetting trend
The wetting trend in May is a direct result of earlier onset of South Asian summer monsoon associated with the phase transition of Interdecadal Pacific Oscillation
Policy makers need reliable future climate projection for adaptation purposes. A clear separation of sources of uncertainty also helps narrow the projection uncertainty. However, it remains unclear ...for monsoon precipitation projections. Here we quantified the contributions of internal variability, model uncertainty, and scenario uncertainty to the ensemble spread of global land monsoon precipitation projections using Coupled Model Intercomparison Project Phase 5 (CMIP5) models and single‐model initial‐condition large ensembles (SMILEs). For mean precipitation, model uncertainty (contributing ~90%) dominates the projection uncertainty, while the contribution of internal variability (scenario uncertainty) decreases (increases) with time. The source of uncertainty for extreme precipitation differs from that of mean precipitation mainly in long‐term projection, with the contribution of scenario uncertainty comparable to model uncertainty. Reducing model uncertainty can effectively narrow the monsoon precipitation projection. The internal variability estimates differ slightly among models and methods, the uncertainty partitioning is robust in middle‐long term.
Plain Language Summary
Climate projections are subject to large uncertainty arisen from climate internal variability, model uncertainty, and scenario uncertainty. Understanding the sources of uncertainty is fundamental for narrowing the uncertainty in projections, further leading to more reliable future climate projections required for decision‐making. Focusing on the global land monsoon region, we quantified the contributions of different uncertainty components in the projections of mean and extreme precipitation. For mean precipitation, model uncertainty dominates the projection uncertainty, with a fractional contribution of ~90%, while the contribution of internal variability (scenario uncertainty) decreases (increases) with time. For extreme precipitation, the results are generally similar except that at the end of 21st century the contribution of scenario uncertainty is comparable to model uncertainty. Reductions of model uncertainty by improving model performances or employing high‐skill models can effectively narrow the uncertainty in monsoon precipitation projection.
Key Points
Model uncertainty (contributing ~90%) dominates the uncertainty in monsoon mean and extreme precipitation projections
Reducing model uncertainty and employing high‐skill models can effectively narrow the uncertainty in monsoon precipitation projections
Although internal variability estimates differ slightly among models and methods, the uncertainty partitioning is robust in middle‐long term
Changes in global land monsoon (GLM) precipitation determine the local water resource, affecting two thirds of global population. The future changes in GLM summer precipitation and the sources of ...projection uncertainty under four scenarios are investigated using the Coupled Model Intercomparison Project Phase 6 (CMIP6) models. The GLM summer precipitation is projected to increase by 1.76 ± 1.57% (2.54 ± 2.22%), 1.33 ± 1.97% (3.52 ± 3.05%), 0.96 ± 2.04% (3.51 ± 4.97%), and 1.71 ± 2.38% (5.75 ± 5.92%) in the near (long) term under Shared Socioeconomic Pathway (SSP) 1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5, respectively. The enhancement is caused by thermodynamic responses due to increased moisture, which is partly offset by dynamic responses due to weakened circulation. The uncertainty in GLM precipitation projection is the largest in SSP5–8.5 long‐term projection. The uncertainty of submonsoon precipitation projections is larger than that in GLM precipitation. The uncertainty of monsoon precipitation projection arises from the circulation changes, which can be partly explained by model‐dependent response to uniform sea surface temperature warming.
Plain Language Summary
The changes of monsoon rainfall under a warmer climate receive much attention. Here we revealed the future changes of summer precipitation over global and submonsoon regions in different periods under four new scenarios designed by the Coupled Model Intercomparison Project Phase 6 (CMIP6). In 2021–2040 (2080–2099), the monsoon summer rainfall will increase by about 1.76 ± 1.57% (2.54 ± 2.22%), 1.33 ± 1.97% (3.52 ± 3.05%), 0.96 ± 2.04% (3.51 ± 4.97%), and 1.71 ± 2.38% (5.75 ± 5.92%) under the low, medium, and two high emission scenarios, respectively. At the end of the 21st century, the monsoon rainfall will increase largest in the highest emission scenario with largest spread. Moreover, the spread over each submonsoon region is much larger than that of global land monsoon. The increase of rainfall is associated with the increase of water vapor but offset by the weakened circulation. The spread of rainfall changes is caused by the spread of circulation projection, which is partly caused by the model‐dependent responses of circulation to uniform sea surface temperature warming.
Key Points
Global land monsoon precipitation increase is due to moisture increases, while the uncertainty is due to uncertainty of circulation changes
The uncertainty of circulation mainly comes from model spread in midterm and long‐term projections but from internal variability in near term
Model‐dependent response to uniform sea surface temperature warming is one of the uncertainty sources in land monsoon circulation projection
Unlike traditional finance, digital inclusive finance is committed to integrating digital technology with the financial industry to bring groups originally excluded from traditional finance back into ...formal financial services and provide financial services at reasonable prices and matching needs for all social classes. Digital inclusive finance can effectively reduce the financing costs of SMEs, improve the external financing environment of enterprises, and provide more convenient, equal and perfect financial services for enterprises by using technical support such as "big data + artificial intelligence". The development level of digital inclusive finance is a classical multiple attributes group decision making (MAGDM). The Probabilistic hesitant fuzzy sets (PHFSs), which utilize the possible values and its possible membership degrees to depict decision-makers' behavior in different conditions, has been paid great attention. Though numerous methods have been applied in this environment since PHFSs has been introduced, there are still new fields to be explored. In this paper, we introduce the Cumulative Prospect Theory TODIM (CPT-TODIM) for probabilistic hesitant fuzzy MAGDM(PHF-MAGDM). Meanwhile, the information of entropy is utilized to calculate the weight of attributes, which is used to improve the classical TODIM method. At last, we utilize a numerical case for evaluating the development level of digital inclusive finance to compare the extended CPT-TODIM method with the classical TODIM method.
Extreme high‐temperature events have large socioeconomic and human health impacts. East Asia (EA) is a populous region, and it is crucial to assess the changes in extreme high‐temperature events in ...this region under different climate change scenarios. The Community Earth System Model low‐warming experiment data were applied to investigate the changes in the mean and extreme high temperatures in EA under 1.5°C and 2°C warming conditions above preindustrial levels. The results show that the magnitude of warming in EA is approximately 0.2°C higher than the global mean. Most populous subregions, including eastern China, the Korean Peninsula, and Japan, will see more intense, more frequent, and longer‐lasting extreme temperature events under 1.5°C and 2°C warming. The 0.5°C lower warming will help avoid 35%–46% of the increases in extreme high‐temperature events in terms of intensity, frequency, and duration in EA with maximal avoidance values (37%–49%) occurring in Mongolia. Thus, it is beneficial for EA to limit the warming target to 1.5°C rather than 2°C.
Plain Language Summary
Extreme heats continue to occur as global warming continues in the last several decades. These natural disasters can lead to illnesses and deaths of people and animals and great economic losses. The Paris Agreement called for limiting the global warming bellow 2°C and pursuing efforts to limit it to 1.5°C compared with preindustrial levels. We used a set of simulations to investigate the changes of the mean temperature and extreme heats in 1.5°C and 2°C warmer climates in East Asia and the benefits of limiting global warming to 1.5°C rather than 2°C. We find that the mean warming of East Asia is about 0.2°C higher than global mean. Most densely populated subregions, including eastern China, the Korean Peninsula, and Japan, will see larger extreme heats increase than the other subregions of East Asia. Compared with the 2°C warming climate, the increasing of extreme heats will be reduced over one third in the 1.5°C warming climate.
Key Points
Changes in the mean and extreme high temperatures over East Asia in response to warmings of 1.5°C and 2°C were quantified using the recently released NCAR CESM low‐warming experiment data
Most densely populated subregions, including eastern China, the Korean Peninsula, and Japan, will see larger increases in extreme high‐temperature events than the other subregions of East Asia in terms of intensity, frequency, and duration under 1.5°C and 2°C warming
The 0.5°C lower warming will help avoid 35%‐46% of the increases in the frequency, intensity, and duration of extreme high‐temperature events in East Asia with maximal avoidance values (37%‐49%) occurring in Mongolia
Unlike traditional finance, digital inclusive finance is committed to integrating digital technology with the financial industry to bring groups originally excluded from traditional finance back into ...formal financial services and provide financial services at reasonable prices and matching needs for all social classes. Digital inclusive finance can effectively reduce the financing costs of SMEs, improve the external financing environment of enterprises, and provide more convenient, equal and perfect financial services for enterprises by using technical support such as "big data + artificial intelligence". The development level of digital inclusive finance is a classical multiple attributes group decision making (MAGDM). The Probabilistic hesitant fuzzy sets (PHFSs), which utilize the possible values and its possible membership degrees to depict decision-makers' behavior in different conditions, has been paid great attention. Though numerous methods have been applied in this environment since PHFSs has been introduced, there are still new fields to be explored. In this paper, we introduce the Cumulative Prospect Theory TODIM (CPT-TODIM) for probabilistic hesitant fuzzy MAGDM(PHF-MAGDM). Meanwhile, the information of entropy is utilized to calculate the weight of attributes, which is used to improve the classical TODIM method. At last, we utilize a numerical case for evaluating the development level of digital inclusive finance to compare the extended CPT-TODIM method with the classical TODIM method.
In summer 2018, an extraordinary heat wave with record-breaking high temperatures hit Northeast Asia. However, the contribution of atmospheric circulation to this heat wave remains unknown. In this ...study, we quantify the contribution of circulation by using the flow analogue method. It is found that Northeast China, Korea and Japan were the most affected areas by the heat event, from daily to monthly timescales. The persistent high temperature was associated with an anticyclonic anomaly over Northeast Asia, related to the record-breaking northward shift of the western Pacific subtropical high (WPSH). The persistent anomalous anticyclone played a dominant role in this heat event, explaining half of the magnitude of the heat event. Both thermodynamical change and dynamical change in recent decades have increased the probability of occurrence of this kind of heat event over Northeast Asia. Specifically, the change in dynamical flow explains a fraction of less than 20% of the increases in probability of heat events. The contribution of thermodynamical changes to heat events generally increases with the rarity of the extreme event.
Abstract
Projected changes of future precipitation extremes exhibit substantial uncertainties among climate models, posing grand challenges to climate actions and adaptation planning. Practical ...methods for narrowing the projection uncertainty remain elusive. Here, using large model ensembles, we show that the uncertainty in projections of future extratropical extreme precipitation is significantly correlated with the model representations of present-day precipitation variability. Models with weaker present-day precipitation variability tend to project larger increases in extreme precipitation occurrences under a given global warming increment. This relationship can be explained statistically using idealized distributions for precipitation. This emergent relationship provides a powerful constraint on future projections of extreme precipitation from observed present-day precipitation variability, which reduces projection uncertainty by 20–40% over extratropical regions. Because of the widespread impacts of extreme precipitation, this has not only provided useful insights into understanding uncertainties in current model projections, but is also expected to bring potential socio-economic benefits in climate change adaptation planning.
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