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Accurate detection and attribution of past climate change are crucial for projecting future climate change and formulating proper policies. In this study, we show that the warming of the tropical Indian Ocean contributes to the observed wetting trend in the Tibetan plateau. The warming tropical Indian Ocean can lead to more precipitation around the Arabian Sea. The associated diabatic heating triggers the cyclonic atmospheric response in the lower troposphere over the Arabian Sea and eastern Africa. It also causes the enhancement and westward extension of the western North Pacific subtropical high. The in‐between airflow transports more moisture northward to the plateau, leading to the increased precipitation over the plateau. These large‐scale circulation patterns can be detected from the long‐term trends based on the observations and the large‐ensemble historical simulations. They can also be simulated by an atmospheric general circulation model forced by the observed warming merely in the tropical Indian Ocean. Plain Language Summary: The Tibetan plateau, often referred to the "Asian water tower," is the source region of many major rivers in Asia. It has experienced an increasing precipitation trend over the past few decades. In this study, we show that the warming tropical Indian Ocean contributes to this wetting trend. The warming tropical Indian Ocean can cause more precipitation around the Arabian Sea. The associated diabatic heating not only triggers an anomalous cyclone in the lower troposphere around the Arabian Sea and eastern Africa, but also causes the enhancement and westward extension of western North Pacific subtropical high. Consequently, the northward airflow between them transports more moisture to the plateau and causes more precipitation there. Our findings underscore the significant role of the warming tropical Indian Ocean in shaping the changing climate under global warming. Further research efforts are warranted to deepen our understanding of this phenomenon. Key Points: The warming tropical Indian Ocean increases the precipitation over the Arabian SeaThe associated large‐scale circulation anomalies transport more moisture northward to the plateauConsequently, more moisture converges over the plateau, leading to the increased precipitation [ABSTRACT FROM AUTHOR]

Understanding both positive and negative impacts of climate change is essential for comprehensively assessing and well adapting to the impacts of changing climate. Conventionally, climate warming is revealed to negatively impact human activities. Here, we reveal that human beings' performance in anaerobic sports may benefit from climate warming. Using global weather observation and athletes' performance datasets, we show that world-top athletes' performances in nearly all athletics anaerobic events (i.e., sprints, jumps and throws) substantially improve as ambient temperature rises. For example, 100 m performance monotonically improves by 0.26 s as ambient temperature rises from 11.8° to 36.4 °C. Using Coupled Model Intercomparison Project Phase 6 datasets, we further show that global warming can substantially improve world-top athletes' performance in eleven of the thirteen Olympics athletics anaerobic events by 0.27%–0.88% and 0.14–0.48% under high-emission and medium-emission scenarios, respectively, during 1979–2100. Among them, the improvements for 100 m are 0.59% (0.063 s) and 0.32% (0.034 s), respectively. Mechanism analysis shows that the warmed ambient atmosphere can improve competitors' performance through expanding the air and thus reducing the air resistance to the competitors and throwing implements for hummer throw and all the sprints, hurdling and jumps. Quantitative analysis estimates that this thermodynamic process is essential for the impacts of warmed ambient atmosphere on the performances in these events as physiological processes are. [ABSTRACT FROM AUTHOR]

Climate warming and anthropogenic disturbances result in permafrost degradation in cold regions, including in the Qilian Mountains. These changes lead to extensive hillslope thermokarst (HT) formation, such as retrogressive thaw slumps, active-layer detachment slides, and thermal erosion gullies. These in turn cause, e.g., degradation of local vegetation, economic losses, infrastructure damages, and threats to human safety. However, despite its importance, there is currently no thermokarst inventory for the Qilian Mountains. Through manual visual interpretation and field validation, we therefore produce the first quantification of HT features. We count a total of 1064 HT features, with 67 % located in the upper reaches of the Heihe River basin, which encompasses ∼ 13 % of the Qilian Mountains region. We further identified that 187 HT features (18 %) existed before 2010, while the remaining 874 (82 %) were initiated in the recent period. More specifically, 392 sites (37 %) were initiated during 2010–2015 and 482 (45 %) after 2015. Thermokarst terrain is observed primarily in areas with shallow active-layer depths (average thickness 2.98 m) on northern shaded slopes of 3–25°, with low solar radiation and moderate elevations ranging from 3200 to 4000 m. This first inventory of HT features is an important and missing piece in documenting changes on the Qinghai–Tibetan Plateau, and this new dataset also provides an important basis for further studies, such as automated extraction of HT features, susceptibility analysis of HT, and estimation of losses caused by HT. The datasets are available from the National Tibetan Plateau/Third Pole Environment Data Center and can be downloaded from 10.11888/Cryos.tpdc.300805 (Peng and Yang, 2023). [ABSTRACT FROM AUTHOR]

This study aims to detect atmospheric rivers (ARs) around the world by developing a deep‐learning ensemble method using AR catalogs of the ClimateNet data set. The ensemble method, based on 20 semantic segmentation algorithms, notably reduces the bias of the testing data set, with its intersection over union score being 1.7%–10.1% higher than that of individual algorithms. This method is then applied to the Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets to quantify AR frequency and its related precipitation in the historical period (1985–2014) and future period (2070–2099) under the Shared Socioeconomic Pathways 5–8.5 warming scenario. The six key regions, which are distributed in different continents of the globe and greatly influenced by ARs, are particularly highlighted. The results show that CMIP6 multi‐model mean with the deep‐learning ensemble method reasonably reproduces the observed AR frequency. In most key regions, both heavy precipitation (90–99 percentile) and extremely heavy precipitation (>99 percentile) are projected to increase in a warming climate mainly due to the increased AR‐related precipitation. The AR contributions to future heavy and extremely heavy precipitation increase range from 145.1% to 280.5% and from 36.2% to 213.5%, respectively, indicating that ARs should be taken into account to better understand the future extreme precipitation changes. Plain Language Summary: Atmospheric rivers (ARs) play a key role in determining the global water cycle and regional precipitation in midlatitudes. Identifying their occurrences and possible changes is therefore critical to understanding the hydroclimate and its change. However, there exist different AR detection tools applying different methods or using different thresholds. The disparities between the outputs of these methods are large and often difficult to reconcile. This study first develops a deep‐learning ensemble method to identify ARs and then applies it to study the AR frequency and its related precipitation in the state‐of‐the‐art climate model simulations for historical and future climates. The results show that AR frequency is reasonably well reproduced by the multi‐model mean. More importantly, it is projected to increase in the future at both the global and regional scales. The six key regions, in which precipitations are robustly influenced by ARs, show that both heavy and extremely heavy precipitation are projected to increase, primarily due to the enhanced AR‐related precipitation. Key Points: An ensemble method with multiple deep‐learning algorithms is established to detect atmospheric rivers (ARs)The ensemble method outperforms individual deep‐learning algorithms in AR detectionThe increase in AR‐related precipitation largely determines the future increase in heavy and extremely heavy precipitation in midlatitudes [ABSTRACT FROM AUTHOR]

Currently, the Arctic is undergoing a significant warming, which has exerted widespread impacts on global climate. Although many mechanisms responsible for the Arctic warming have been proposed, the impacts of the multi‐decadal change of tropical sea surface temperature receive little attention. Here we use numerical experiments to elucidate that the Indian Ocean (IO) warming may contribute to the Arctic warming. Through enhancing the Atlantic Meridional Overturning Circulation, the IO warming remotely induces more ocean heat transport from the North Atlantic to the Arctic. The resulted upper ocean warming dominates the surface warming in the Arctic. Additionally, despite the net negative contribution of the atmospheric heat transport, more warm air is conveyed into the Kara Seas, North Eurasia, and North America sectors, contributing to the local warming. The results propose a new mechanism to interpret the Arctic warming and indicate the important remote impacts of the tropical IO warming. Plain Language Summary: The Arctic warming is a significant phenomenon in the context of global warming, which not only impacts the local ecosystem but also influences global climate. Improved understanding of its causes is important to the protection of the Arctic ecosystem and the forecast of global climate. Although many previous studies have proposed various mechanisms to interpret the Arctic warming, its causes are still not fully understood. In this study, we find that the Indian Ocean (IO) warming is also a possible contributor to the Arctic warming. Through enhancing the Atlantic Meridional Overturning Circulation, the IO warming remotely induces more ocean heat transport from the North Atlantic to the Arctic and then contributes to the Arctic warming. Additionally, the southerly winds in the high latitudes in response to the IO warming, transport more warm air into the Kara Seas, North Eurasia and North America and contributes to the local warming. The present study indicates the IO warming may also contribute to the Arctic warming. A better understanding of the remote impacts of tropical oceans may foster the comprehensive understanding of the complicated reasons for the Arctic warming. Key Points: Rapid warming in the Indian Ocean (IO) may contribute to the Arctic warming through both oceanic and atmospheric pathwaysMore ocean heat is transported from the North Atlantic to the Arctic due to enhanced Atlantic Meridional Overturning Circulation in response to the IO warmingSoutherly winds in the high latitudes in response to the IO warming convey more warm air into parts of the Arctic [ABSTRACT FROM AUTHOR]

• We attempted to study the growth dynamics of the retrogressive thaw slump (RTS). • This study presents annual RTS observations in Qinghai-Tibetan Plateau (QTP). • Total number and affected areas of RTSs exhibited a major increase in 2016. • RTS headwall retreat rate was significantly affected by climatic and terrain factors. With persistent climate warming, a rapid increase in retrogressive thaw slump (RTS) activity has been observed in the permafrost region of the Qinghai-Tibetan Plateau (QTP). However, the initiation and growth dynamics of these RTSs have not yet been fully investigated. In this study, annual RTS observations from 2013 to 2021 within the Hoh Xil region (HXR), based on field investigations and satellite imagery interpretations, are presented. The total number and affected areas of RTSs in the HXR significantly increased during the last 8 years, and such an increase mainly occurred in 2016 when an anomalously high air temperature appeared during the thawing season, which induced the massive occurrence of active layer detachment slides. The mean headwall retreat rate of RTSs in the HXR ranged from 2.4–3.2 m/y from 2013, or their initialization, to 2021, and the highest headwall retreat occurred in the first 2–3 years after RTS initiation. In addition, the headwall retreat rate of RTSs in the study region was significantly affected by the climatic factors, including average daily air temperature, thawing degree days, and cumulative precipitation and also controlled by the ratio of slump floor slope to undisturbed terrain slope, the headwall height, and permafrost conditions. The study's findings can serve as a reference for hazard mitigation and regional carbon cycle assessment of the QTP. [ABSTRACT FROM AUTHOR]

Extreme El Niño events severely disrupt the global climate, causing pronounced socio-economic losses. A prevailing view is that extreme El Niño events, defined by total precipitation or convection in the Niño3 area, will increase 2-fold in the future. However, this projected change was drawn without removing the potential impacts of Coupled Model Intercomparison Project phase 5 (CMIP5) models' common biases. Here, we find that the models' systematic biases in simulating tropical climate change over the past century can reduce the reliability of the projected change in the Pacific sea surface temperature (SST) and its related extreme El Niño frequency. The projected Pacific SST change, after removing the impacts of 13 common biases, displays a 'La Niña-like' rather than 'El Niño-like' change. Consequently, the extreme El Niño frequency, which is highly linked to the zonal distribution of the Pacific SST change, would remain mostly unchanged under CMIP5 warming scenarios. This finding increases confidence in coping with climate risks associated with global warming. [ABSTRACT FROM AUTHOR]

Future changes in the frequency of extreme drought events are of vital importance for risk assessment and relevant policy making. But a reliable estimation of their probability is intrinsically challenging due to limited available observations or simulations. Here, we use two large ensemble simulations, 50 members from CanESM2 and 40 members from CESM1 under the future RCP8.5 scenario, to elaborate a reliable projection of the 100-yr drought events (once in a century) under different warming levels. It is however necessary to first remove systematic biases for the simulated temperature and precipitation through a bias-correction method based on quantile mapping. Droughts are diagnosed with the standardized precipitation evapotranspiration index (SPEI), which considers both precipitation and potential evapotranspiration (PET, involving temperature). The results show that the frequency of extreme droughts increases with the continued global warming. Some differences between the two ensembles are also observed, especially for high warming levels. The China-averaged probability of 100-yr droughts that occur once in a century in the current climate increase by a factor of 1.52 (1.44) and 1.90 (2.02) under 1.5°C and 2°C warming levels in CanESM2-LE (CESM1-LE), respectively. A simple statistical scheme shows that the increasing future risk of extreme droughts is mainly due to the increasing effect of PET on the occurrence of extreme drought events, while the effect of precipitation almost keeps constant with global warming. [ABSTRACT FROM AUTHOR]

The occurrence of the 2017/2018 La Niña, following a weak‐to‐neutral La Niña in boreal winter 2016/2017, was surprising. Based on observational records and multiple linear regression analysis for the Pacific zonal wind tendency (dU/dt), this study investigates possible reasons why the La Niña condition suddenly happened in late 2017. Similar to previous four double‐peaked La Niña events (1983–1985, 1998–2000, 2007–2009, and 2010–2012), we find that the multiyearly persistent easterly anomaly in the central equatorial Pacific is a key condition to the development of the second La Niña. The occurrence of the 2017/2018 La Niña results from large warm sea surface temperature (SST) anomalies in the tropical Indian and Atlantic Oceans that act to force the persistent easterly anomaly in the Pacific via modifying the Walker Circulations. About 24% of the variance of the Pacific dU/dt can be statistically explained by the tropical Indian Ocean and Atlantic SST anomalies. Plain Language Summary: The 2017/2018 La Niña appears to be surprising, given that an El Niño‐like condition has already developed in the first half of 2017 but actually in opposite to most models' forecasts that issued a false alarm of an El Niño. Previous studies suggested that both the tropical Indian and Atlantic Oceans have exhibited a rapid warming in recent decades, which have caused an easterly trend in the central Pacific. In this study, we examine the possible contributions of the tropical Indian Ocean and Atlantic SSTs to the occurrence of the second La Niña in 2017/2018. Our results highlight the importance of the SST warming in the tropical Indian and Atlantic Oceans for the occurrence of the second La Niña under rapid SST warming in the two basins during recent decades. Key Points: Persistent easterly anomaly in the central equatorial Pacific is a key condition to the occurrence of the second La NiñaRapid SST warming in the tropical Indian and Atlantic Oceans acts to strengthen the persistent easterly anomalyAbout 24% of the variance of the dU/dt in the central equatorial Pacific during 1980‐2017 can be explained by the IO and AO SSTAs [ABSTRACT FROM AUTHOR]

Utilizing the specially designed low‐warming experiments of the fully coupled Community Earth System Model, we investigate the evolutions of Eurasian climate and extreme events if global mean temperature would stabilize at 1.5 °C and 2 °C above preindustrial levels or overshoot the 1.5 °C (1.5 °C OS) threshold. We find that distinctive evolutions of surface temperature (TS) and extreme events appear in different regions of Eurasia, particularly over East China and Northern Eurasia. In the course of global warming, before global mean temperature stabilizes, the two regions display similar changes of TS and extreme events. However, after global warming halts, the two regions experience distinctive evolutions of local warming and extreme events. Over East China, where the adjacent ocean exhibits stronger‐than‐global mean warming, the local TS and both the strength and frequency of heat extremes keep increasing continuously. The extreme precipitation intensity increases even more rapidly compared to the change of heat extremes. In stark contrast, TS and heat extremes intensity over northern Eurasia decrease in both the 1.5 °C and 1.5 °C OS cases, except that the extreme precipitation experiences little change. We find that the most vulnerable period over northern Eurasia is the transition period, in which TS increases till its maximum and then decreases. The heat extremes during the transition period are also stronger and more frequent compared to the end of the 21st century over northern Eurasia. Plain Language Summary: Utilizing the specially designed model experiments, we investigate the evolutions of Eurasian climate and extreme events if global mean temperature would stabilize at 1.5 °C and 2 °C above pre‐industrial levels. We find that distinctive evolutions of surface temperature (TS) and extreme events appear in different regions of Eurasia, particularly over East China and Northern Eurasia. Before global mean temperature stabilizes, the two regions display similar changes of TS and extreme events. However, after global warming halts, the two regions experience distinctive evolutions of local warming and extreme events. Over East China, adjacent a stronger‐than‐global mean ocean warming, the local TS and both the strength and frequency of heat extremes keep increase continuously. The extreme precipitation intensity increases even more rapidly compared to the change of heat extremes. In stark contrast, TS and heat extremes intensity over northern Eurasia decrease at 1.5 °C, except that the extreme precipitation experiences little change. We find that the most vulnerable period over northern Eurasia is the transition period, in which TS increases till its maximum and then decreases. The heat extremes during the transition period are also stronger and more frequent compared to the end of the 21st century over northern Eurasia. Key Points: Distinctive regional changes would occur over Eurasia, when global mean temperature stabilizes at 1.5 °CEast China would experience amplified warming and more extreme events, in association with strong SST warming in the adjacent oceanNorthern Eurasia would have transitions from increase to decrease in mean and extreme surface temperatures [ABSTRACT FROM AUTHOR]

The distribution and variations of permafrost in the Xidatan region, the northern permafrost boundary of the Qinghai-Tibet Plateau, were examined and analyzed using ground penetrating radar (GPR), borehole drilling, and thermal monitoring data. Results from GPR profiles together with borehole verification indicate that the lowest elevation limit of permafrost occurrence is 4369 m above sea level in 2012. Compared to previous studies, the maximal rise of permafrost limit is 28 m from 1975 to 2012. The total area of permafrost in the study region has been decreased by 13.8%. One of the two previously existed permafrost islands has disappeared and second one has reduced by 76% in area during the past ~40 years. In addition, the ground temperature in the Xidatan region has increased from 2012 to 2016, with a mean warming rate of ~0.004°C a−1 and ~0.003°C a−1 at the depths of 6 and 15 m, respectively. The rising of permafrost limit in the Xidatan region is mainly due to global warming. However, some non-climatic factors such as hydrologic processes and anthropic disturbances have also induced permafrost degradation. If the air temperature continues to increase, the northern permafrost boundary in the Qinghai-Tibet Plateau may continue rising in the future. [ABSTRACT FROM AUTHOR]

Over the recent three decades sea surface temperate (SST) in the eastern equatorial Pacific has decreased, which helps reduce the rate of global warming. However, most CMIP5 model simulations with historical radiative forcing do not reproduce this Pacific La Niña-like cooling. Based on the assumption of “perfect” models, previous studies have suggested that errors in simulated internal climate variations and/or external radiative forcing may cause the discrepancy between the multi-model simulations and the observation. But the exact causes remain unclear. Recent studies have suggested that observed SST warming in the other two ocean basins in past decades and the thermostat mechanism in the Pacific in response to increased radiative forcing may also play an important role in driving this La Niña-like cooling. Here, we investigate an alternative hypothesis that common biases of current state-of-the-art climate models may deteriorate the models’ ability and can also contribute to this multi-model simulations-observation discrepancy. Our results suggest that underestimated inter-basin warming contrast across the three tropical oceans, overestimated surface net heat flux and underestimated local SST-cloud negative feedback in the equatorial Pacific may favor an El Niño-like warming bias in the models. Effects of the three common model biases do not cancel one another and jointly explain ~50% of the total variance of the discrepancies between the observation and individual models’ ensemble mean simulations of the Pacific SST trend. Further efforts on reducing common model biases could help improve simulations of the externally forced climate trends and the multi-decadal climate fluctuations. [ABSTRACT FROM AUTHOR]

The Indian Ocean Dipole (IOD) can affect the El Niño-Southern Oscillation (ENSO) state of the following year, in addition to the well-known preconditioning by equatorial Pacific Warm Water Volume (WWV), as suggested by a study based on observations over the recent satellite era (1981-2009). The present paper explores the interdecadal robustness of this result over the 1872-2008 period. To this end, we develop a robust IOD index, which well exploits sparse historical observations in the tropical Indian Ocean, and an efficient proxy of WWV interannual variations based on the temporal integral of Pacific zonal wind stress (of a historical atmospheric reanalysis). A linear regression hindcast model based on these two indices in boreal fall explains 50 % of ENSO peak variance 14 months later, with significant contributions from both the IOD and WWV over most of the historical period and a similar skill for El Niño and La Niña events. Our results further reveal that, when combined with WWV, the IOD index provides a larger ENSO hindcast skill improvement than the Indian Ocean basin-wide mode, the Indian Monsoon or ENSO itself. Based on these results, we propose a revised scheme of Indo-Pacific interactions. In this scheme, the IOD-ENSO interactions favour a biennial timescale and interact with the slower recharge-discharge cycle intrinsic to the Pacific Ocean. [ABSTRACT FROM AUTHOR]

Oceanic vertical mixing is known to influence the state of the equatorial ocean which affects the climate system, including the amplitude of El Niño/Southern Oscillation (ENSO). Recent measurements of ocean currents at high vertical resolution capture numerous small vertical scale structures (SVSs) within and above the equatorial thermocline that contribute significantly to vertical mixing but which are not sufficiently resolved by coarse resolution ocean models. We investigate the impact of the vertical mixing induced by the SVSs on the mean state and interannual variability in the tropical Pacific by using a coupled general circulation model. The vertical mixing induced by the SVSs is represented as an elevated vertical diffusivity from the surface down to the 20 °C isotherm depth, a proxy for the depth of the thermocline. We investigate different forms for the elevated mixing. It is found that the SVS-induced mixing strongly affect the mean state of the ocean leading to a warming of sea surface temperature (SST) and associated deepening and sharpening of the thermocline in the eastern equatorial Pacific. We find that the SST warming induced by the elevated mixing is further strengthened through the Bjerknes feedback and SST-shortwave flux feedback. We also find a reduction in the number of large amplitude ENSO events and in certain cases an increase in the skewness of ENSO. [ABSTRACT FROM AUTHOR]

The growth and decay mechanisms of subtropical dipole modes in the southern Indian and South Atlantic Oceans and their impacts on southern African rainfall are investigated using results from a coupled general circulation model originally developed for predicting tropical climate variations. The second (most) dominant mode of interannual sea surface temperature (SST) variations in the southern Indian (South Atlantic) Ocean represents a northeast-southwest oriented dipole, now called subtropical dipole mode. The positive (negative) SST interannual anomaly pole starts to grow in austral spring and reaches its peak in February. In austral late spring, the suppressed (enhanced) latent heat flux loss associated with the variations in the subtropical high causes a thinner (thicker) than normal mixed layer thickness that, in turn, enhances (reduces) the warming of the mixed layer by the climatological shortwave radiation. The positive (negative) pole gradually decays in austral fall because the mixed layer cooling by the entrainment is enhanced (reduced), mostly owing to the larger (smaller) temperature difference between the mixed layer and the entrained water. The increased (decreased) latent heat loss due to the warmer (colder) SST also contributes to the decay of the positive (negative) pole. Although further verification using longer observational data is required, the present coupled model suggests that the South Atlantic subtropical dipole may play a more important role in rainfall variations over the southern African region than the Indian Ocean subtropical dipole. [ABSTRACT FROM AUTHOR]

Abstract: Recent years saw the global wave of new low-carbon economy which is a new strategic measure to cope with global warming, and it has gained lots of concerns from many government s. China is undertaking the “common, but different responsibility for global climate change” and it has made a lot of guidelines of low-carbon economy development. Under this circumstance, as the most potential sector for low-carbon transformation, Chinese tourism becomes the pioneer to try low-carbon industry construction. According to development of Chinese tourism, the authors first discussed the connotation and denotation of low-carbon tourism industry, and then analyzed the feasibility of promotion of low-carbon tourism in China, and finally proposed the policy design and development idea for low-carbon tourism economy in the aspects of different subjects of government, tourism area, tourists etc. [Copyright &y& Elsevier]

Climate variability in the tropical Indo-Pacific sector has undergone dramatic changes under global ocean warming. Extreme Indian Ocean dipole (IOD) events occurred repeatedly in recent decades with an unprecedented series of three consecutive episodes during 2006–08, causing vast climate and socioeconomic effects worldwide and weakening the historic El Niño–Indian monsoon relationship. Major attention has been paid to the El Niño influence on the Indian Ocean, but how the IOD influences El Niño and its predictability remained an important issue to be understood. On the basis of various forecast experiments activating and suppressing air–sea coupling in the individual tropical ocean basins using a state-of-the-art coupled ocean–atmosphere model with demonstrated predictive capability, the present study shows that the extreme IOD plays a key role in driving the 1994 pseudo–El Niño, in contrast with traditional El Niño theory. The pseudo–El Niño is more frequently observed in recent decades, coincident with a weakened atmospheric Walker circulation in response to anthropogenic forcing. The study’s results suggest that extreme IOD may significantly enhance El Niño and its onset forecast, which has being a long-standing challenge, and El Niño in turn enhances IOD and its long-range predictability. The intrinsic El Niño–IOD interaction found here provides hope for enhanced prediction skill of both of these climate modes, and it sheds new light on the tropical climate variations and their changes under the influence of global warming. [ABSTRACT FROM AUTHOR]

Over the recent three decades sea surface temperate (SST) in the eastern equatorial Pacific has decreased, which helps reduce the rate of global warming. However, most CMIP5 model simulations with historical radiative forcing do not reproduce this Pacific La Niña-like cooling. Based on the assumption of "perfect" models, previous studies have suggested that errors in simulated internal climate variations and/or external radiative forcing may cause the discrepancy between the multi-model simulations and the observation. But the exact causes remain unclear. Recent studies have suggested that observed SST warming in the other two ocean basins in past decades and the thermostat mechanism in the Pacific in response to increased radiative forcing may also play an important role in driving this La Niña-like cooling. Here, we investigate an alternative hypothesis that common biases of current state-of-theart climate models may deteriorate the models' ability and can also contribute to this multi-model simulations-observation discrepancy. Our results suggest that underestimated inter-basin warming contrast across the three tropical oceans, overestimated surface net heat flux and underestimated local SST-cloud negative feedback in the equatorial Pacific may favor an El Niño-like warming bias in the models. Effects of the three common model biases do not cancel one another and jointly explain ~50% of the total variance of the discrepancies between the observation and individual models' ensemble mean simulations of the Pacific SST trend. Further efforts on reducing common model biases could help improve simulations of the externally forced climate trends and the multi-decadal climate fluctuations. [ABSTRACT FROM AUTHOR]

El Nino and La Nina strongly affect the year-to-year variability of global climate, which exerts intense pressure on water resources and environmental management in a changing climate. Well-known examples include the severe floods in Australia in 2010-11 and 1998-2000 in association with multi-yearly persistent La Nina events, and a strong drought in 2002 in association with El Nino. Growing evidence suggests that some ENSO events may be predictable at lead times beyond one to two years, which is much longer than the forecasts currently issued by most operational forecast centers worldwide. However, it is still unclear how well ENSO can be predicted at multi-year timescales and what essential dynamics underpins such multiyear predictability. Based on a high-resolution coupled model forecast system (60km grid mesh for atmosphere and 25km grid mesh for ocean), we conducted three sets of ensemble hindcast experiments with lead times up to 16, 36, and 66 months, respectively. Results suggest that, despite considerable model bias in simulating the annual mean states and seasonal cycle of the Indo-Pacific climate, ENSO over the past 35 years can be skillfully predicted out to at least 16 months ahead. Some ENSO events can be well predicted at a multi-year lead. In addition, the results also show good skill in predicting global warming related signals at multi-year timescales. [ABSTRACT FROM AUTHOR]

Rapid atmospheric warming changes the thermal conditions of permafrost over the Northern Hemisphere (NH), including ground temperature warming and ground ice thawing. This warming and thawing of ice-rich permafrost damages existing infrastructure and poses a threat to sustainable development. Bearing capacity (BC) loss and ground subsidence (GS) due to permafrost thawing are two major risks to the infrastructure and key indexes for risk assessment. However, current information on the BC and GS is too coarse, restricted to the Arctic, and scarce for future periods. The aim of this study was to address these gaps by presenting spatial data on the BC and GS for current and future periods across the NH at a resolution of 1 km. A machine learning-based approach was developed to simulate permafrost thermal dynamics under four climate scenarios (SSPs 1–2.6, 2–4.5, 3–7.0, and 5–8.5). The associated changes in the BC and GS were estimated based on changes in the permafrost temperature at or near the depth of zero annual amplitude (MAGT) and active-layer thickness (ALT). The results indicate a continuous increase in MAGT and ALT by 2.3 °C (SSPs1–2.6) to 7.6 °C (SSPs5–8.5) and 16.0 cm (SSPs1–2.6) to 51.0 cm (SSPs5–8.5), respectively, at the end of the 21ts century. This permafrost degradation will lead to a high potential BC loss of 37.8% (SSPs1–2.6) to 40.2% (SSPs5–8.5) on average over 2041–2060, and up to 60.5% (SSPs1–2.6) to 92.2% (SSPs5–8.5) in 2081–2100. The produced average GS is approximately 1.0 cm in 2021–2040, and further up to 1.5 cm (SSPs1–2.6) to 4.7 cm (SSPs5–8.5) in 2081–2100, with notable variations across the permafrost region. These forecasts provide new opportunities to assess future permafrost changes and associated risks and costs with climate warming. [Display omitted] • Machine learning and geotechnical models were developed and utilized at a 1 km resolution. • Permafrost will notably degrade under a warming and wetting climate. • High bearing capacity loss and ground subsidence is projected to occur. [ABSTRACT FROM AUTHOR]

Air, ground surface, and permafrost surface temperatures are important components of the permafrost thermal regime. However, ground temperatures from one or two boreholes are commonly considered representative of site conditions in permafrost studies despite significant variations in local surface conditions. This makes the evaluation of site-scale temperature variations important for improving the accuracy of permafrost modelling efforts. In this study we analyzed the variability in near-surface ground temperatures in a warming permafrost region using high spatial density borehole measurements to capture variations in surface conditions. Ground temperatures were collected from 72 boreholes drilled to 5 m depth at 8 sites in Beiluhe Basin, Qinghai-Tibet Plateau. Six sites straddled an alpine meadow ecotone between well- and sparsely-vegetated ground, and two sites were located on slopes with opposing aspects. Air temperatures at the 8 sites were similar with annual mean values ranging from −2.6 to −3.0 °C in 2016–18. In contrast, annual mean surface temperatures exhibited greater variation between sites, so that surface offsets were also variable. Ground surface temperatures were highest at a sloping sunny site, and lowest at a north-facing shady site. The results indicated that surface temperatures were strongly controlled by slope aspect. In contrast, the expected effect of vegetation cover shading was not distinguishable because of variations in soil moisture content between sites. Deeper temperatures at the permafrost surface and at 5 m depth exhibited a similar trend among sites except in an unusual warm transitional area where eolian erosion disturbed the surface vegetation cover. The detailed ground temperature records characterizing within- and between-site variations could be used in future to support the calibration and validation of numerical models of permafrost distribution. • Ground temperatures to 5 m depth in eight plots were collected over two years. • Intra-unit variations in hydrothermal were examined by multiple measurements. • Thermal differences between sites across varying geomorphic units were investigated. • Data contribute to an improved field characterization of the ground thermal regime. [ABSTRACT FROM AUTHOR]

The article presents a summary report on global climate that represents the 18th annual State of the Climate published by the National Oceanic and Atmospheric Administration's National Climactic Data Center. It highlights the most salient events and overall climate conditions of the year 2007 which include remarkable weather events, assessment of temperature and precipitation anomalies, and reports on some of the primary features and parameters of the global climate system. It discusses global conditions into five sections which include global climate, global oceans, the tropics, the poles, and regional climates.