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The middle reaches of the Lancang‐Mekong River Basin (M‐LMRB) experienced a record‐breaking drought event in 2019, resulting in significant economic losses of approximately 650 million dollars and affecting a population of 17 million. However, the anomalous circulation and transportation processes of water vapor, which may have played a crucial role in inducing the extreme drought, have not been fully studied. In this study, we analyze the water vapor circulation during the 2019 drought event using the land‐atmosphere water balance and a backward trajectory model for moisture tracking. Our results indicate that the precipitation in the M‐LMRB from May to October 2019 was only 71.9% of the long‐term climatological mean (1959–2021). The low precipitation during this drought event can be attributed to less‐than‐normal external water vapor supply. Specifically, the backward trajectory model reveals a decrease in the amount of water vapor transported from the Indian Ocean, the Bay of Bengal, and the Pacific Ocean, which are the main moisture sources for precipitation in the region. Comparing the atmospheric circulation patterns in 2019 with the climatology, we identify anomalous anticyclone conditions in the Bay of Bengal, anomalous westerlies in the Northeast Indian Ocean, and an anomalous cyclone in the Western Pacific Ocean, collectively facilitating a stronger export of water vapor from the region. Therefore, the dynamic processes played a more significant role than thermodynamic processes in contributing to the 2019 extreme drought event. Plain Language Summary: In 2019, a record‐breaking drought hit the M‐LMRB, leading to significant economic losses and affecting a large population. This study explores the water vapor circulation during this drought using land‐atmosphere water balance and a backward trajectory model. Findings show that precipitation from May to October 2019 was only seventy percent of the average from 1959 to 2021. The drought's severity was mainly due to a lack of water vapor from key sources: the Indian Ocean, the Bay of Bengal, and the Pacific Ocean. Anomalous weather patterns—an anticyclone in the Bay of Bengal, unusual westerlies in the Northeast Indian Ocean, and a cyclone in the Western Pacific—led to a significant reduction in water vapor reaching the region. This indicates that dynamic atmospheric processes played a larger role in causing the extreme drought than thermodynamic ones. These insights help improve understanding and prediction of droughts in Southeast Asia, particularly under changing climate conditions. Key Points: Reduced external water vapor transport primarily leads to negative precipitation anomaliesThere has been a reduction in water vapor originating from the Indian Ocean, Bay of Bengal, and Pacific OceanThe reduction in water vapor transport is primarily influenced by dynamic factors rather than thermodynamic ones [ABSTRACT FROM AUTHOR]

Global warming has intensified the intensity of compound drought‐hot extremes (CDHEs), posing more severe impacts on human societies and ecosystems than individual extremes. The vulnerability of global terrestrial ecosystems under CDHEs, along with its key influencing factors, remains poorly understood. Based on multiple remote sensing data, we construct a Vine Copula model to appraise vegetation vulnerability under CDHEs, and attribute it to climatic and biotic factors for five different vegetation types. High vulnerability is detected in central and southern regions of North America, eastern and southern regions of South America, Southern Africa, northern and western Europe, and northern and eastern Australia. The drier the climate, the higher will be the vulnerability. Furthermore, biodiversity and biomass are key biotic factors influencing the vulnerability of various vegetation types, such that ecosystems with richer biodiversity and higher biomass have lower vulnerability to CDHEs. The findings deepen understanding of terrestrial ecosystem response to CDHEs. Plain Language Summary: Drought and hot‐related extremes often coincide or follow one another, known as compound drought‐hot extremes (CDHEs), adversely affecting various vegetation processes. Thus, investigating the response relationship between vegetation dynamics and CDHEs is critical for maintaining the sustainable development of ecosystems under the background of climate warming. High ecosystem vulnerability is detected in central and southern regions of North America, eastern and southern regions of South America, Southern Africa, northern and western Europe, and northern and eastern Australia. Climatic factors (precipitation, arid index, temperature, and radiation) dominate the vulnerability of all vegetation types. The drier the climate, the higher will be the vulnerability of vegetation to CDHEs. Furthermore, biodiversity and biomass are key biotic factors influencing the vulnerability. The results provide us with essential insights for managing and adapting terrestrial ecosystems against climate change and are of interest to a wide range of audiences, including but not limited to ecologists, hydrologists, and climatologists. Key Points: A framework is developed to estimate the vegetation vulnerability in response to compound drought‐hot extremes and attribute it to various factorsVegetation vulnerability is higher for grasses and shrubs than for evergreen and deciduous forestsVegetation vulnerability is both affected by climate and biotic factors, but climate factors are more dominant [ABSTRACT FROM AUTHOR]

Recent extremely heavy precipitation has led to substantial economic losses and affected millions of residences in the Lancang‐Mekong River Basin (LMRB). This study analyzed the spatial‐temporal characteristics of the annual maximum precipitation (R1X) of the LMRB and identified the moisture sources and pathways conducive to R1Xs using a Lagrangian back trajectory model. Results show that India Ocean and Bay of Bengal (IO/BOB), local evapotranspiration, and West Pacific Ocean and East China (WP/EC) are the three main moisture transport pathways of the R1Xs in LMRB, contributing 68.3%, 20.4% and 11.3% of the trajectories, respectively. R1Xs in the downstream eastern area are affected by tropical cyclones bringing large amounts of moisture from the WP/EC. As tropical cyclones shifted northward under climate change impact, more extreme precipitation occurred over the LMRB due to moisture coming from WP/EC, but those from the IO/BOB had decreased because of the slowdown of flows across the Equator. Plain Language Summary: Recent extremely heavy precipitation has led to more frequent floods, storm surges, and other natural hazards in the Lancang‐Mekong River Basin, resulting in substantial economic losses and affecting millions of residences. This study used annual maximum precipitation to represent the extreme precipitation and analyzed its spatial‐temporal characteristics and the moisture sources and pathways. Results show that the extreme precipitation of the upstream region mainly occurred in July, while that of the downstream region mainly occurred in August‐September. The moisture pathways of the historical extreme precipitation were identified using a physical‐based model, and are classified into three clusters using a machine‐learning model. West Pacific Ocean and East China, local evapotranspiration, and Indian Ocean and Bay of Bengal (IO/BOB) are the three moisture transport pathways with contributions of 68.3%, 20.4%, and 11.3% to the total pathways. The tropical cyclones bring large amounts of moisture and mainly affect R1Xs in the downstream eastern area. Tropical cyclones shifted northward under climate change impact, and more extreme precipitation occurred over the LMRB due to moisture coming from the West Pacific Ocean and East China, but those from the IO and BOB had decreased because of the slowdown of flows across the Equator. Key Points: The timing of the annual maximum precipitation of the Lancang‐Mekong River Basin (LMRB) varies from July to SeptemberThe extreme precipitation of the LMRB mainly received moisture from the Indian Ocean to the West Pacific OceanTropical cyclones will bring more extreme precipitation to the LMRB under climate change [ABSTRACT FROM AUTHOR]

The Arctic rivers contribute more than one‐third of the total freshwater streamflow into the Arctic Ocean and play an essential role in the heat and mass circulation of the Arctic atmosphere/ocean system. As the Arctic is warming faster than the global average, the streamflow from Arctic basins increases. This study analyzed the streamflow of the three largest Siberian rivers: the Lena, Yenisei, and Ob', at multiple temporal scales. Results show that the annual streamflow of each river basin exhibits statistically significant increasing trends, while the seasonal streamflow of sub‐basins generally decreases in the summer but increases in the winter. Both autocorrelation and long‐term persistency are often found in the streamflow time series, which indicates significant changes in the large‐scale climatological environment. Therefore, wavelet coherence between the streamflow and large‐scale climate patterns, including the El Niño–Southern Oscillation (ENSO), North Pacific pattern (NP), Arctic Oscillation (AO), and the Pacific/North America Pattern (PNA), have been conducted. NP and ENSO are found to have positive relationships with the precipitation and the ratio of potential evapotranspiration over the precipitation. AO and the PNA are found to have positive relationships with the streamflow of the Ob' and Yenisei rivers at decadal and multidecadal scales. This study demonstrates that the existence of nonstationarities within the Siberian streamflow as the combined impact of climate change alters the hydroclimatological and terrestrial environment of Siberia. These findings provide new insights into the mechanisms underlying the hydrologic changes to warming trends and oscillations of climate patterns, which contribute to our understanding and the prediction of streamflow of these northern rivers. [ABSTRACT FROM AUTHOR]

Climate change impacts due to unprecedented rising concentrations of greenhouse gas (GHG) are intensifying and widespread, making extreme climate events more widespread, frequent, and severe. To mitigate the worst consequences of climate warming, herein it is investigated how the global community can collectively achieve a large‐scale, sustained reduction in GHG emissions, and how to effectively move away from a predominantly fossil fuel‐based economy to one dominated by renewable energy? This transition is necessary to achieve the sustainable development goals (SDGs) of United Nations (UN) to ensure resilient and healthy environment for present and future generations, especially the SDG 7 of UN, "Affordable and Clean Energy", set up to achieve global development of modern renewable energy systems. Investment policies and patterns of developed and developing countries in transitioning to energy productions primarily from renewable sources and obstacles such as scale‐up challenges, innovations in new energy systems, policies, financing mechanisms, and implementation strategies are examined. Furthermore, a comprehensive overview of the present global status of hydropower, wind, and solar, the three most significant renewable electricity technologies, as well as their basic operating principles, costs, and potential is conducted. Hydroelectric, wind, and solar power had grown from 3429, 346, and 34 TWh yr−1 in 2010 to 4274, 1598, and 846 TWh yr−1 in 2020, a growth of about 1.25, 4.60, and 24.9 times in a decade, respectively. Strategies to achieve energy systems that are of or near net zero GHG emissions by 2050s through the deployment of renewable energy systems are also investigated. [ABSTRACT FROM AUTHOR]

A coupled atmospheric-hydrologic system models the complex interactions between the land surface and the atmospheric boundary layer and the water-energy cycle from groundwater across the land surface to the top of the atmosphere. A regional climate model called weather research forecasting (WRF) was coupled with a land-surface scheme (Noah) to simulate intensive storms in Alberta of Canada. Accounting for the land-atmosphere feedback enhances the predictability of the fine-tuned WRF-Noah system. Soil moisture, vegetation, and land-surface temperature influence latent and sensible heat fluxes and modulate both thermal and dynamical characteristics of land and the lower atmosphere. WRF was set up in a two-way, 3-domain nested framework so that the output of the outermost domain (D1) was used to run the 2nd domain (D2), and the output of D2 was used to run the innermost, 3rd domain (D3). By this 2-way nesting, D3 and D2 provide the feedback to their outer domains (D2 and D1), respectively. D3 was set at a 3-km resolution adequate to simulate convective storms. WRF-Noah was forced with climate outputs from global climate models (GCMs) for the baseline period 1980–2005. A regional frequency analysis and a quantile-quantile bias correction method were applied to develop intensity-duration-frequency (IDF) curves using precipitation data simulated by WRF-Noah. The simulated baseline precipitation of central Alberta agrees well with observed data from a 13-rain gauge network of the City of Edmonton. The 5th-generation mesoscale atmospheric model (MM5) of National Center for Atmospheric Research was also set up in a 3-domain, but 1-way nesting configuration. As expected, after bias correction, precipitation simulated by MM5 was less accurate than that simulated by WRF-Noah. For storms of short durations and return periods of more than 25 years, both MM5 driven by special reports on emission scenario climate scenarios of coupled model inter-comparison project (CMIP3) and WRF-Noah driven by representative concentration pathway climate scenarios of CMIP5 projected storm intensities in central Alberta to increase from the base period to the 2050s and to the 2080s. [ABSTRACT FROM AUTHOR]