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A severe agricultural drought swept Central Asia in 2021, causing mass die-offs of crops and livestock. The anthropogenic contribution to declines in soil moisture in this region over recent decades has remained unclear. Here we show from analysis of large ensemble simulations that the aggravation of agricultural droughts over southern Central Asia since 1992 can be attributed to both anthropogenic forcing and internal variability associated with the Interdecadal Pacific Oscillation (IPO). Although the negative-to-positive phase transition of IPO before 1992 offset human-induced soil moisture decline, we find that the positive-to-negative phase transition thereafter has doubled the externally forced rate of drying in the early growing season. Human-induced soil moisture loss will probably be further aggravated in the following century due to warming, albeit with increasing precipitation, and our simulations project that this trend will not be counterbalanced by the IPO phase change. Instead, this internal variability could modulate drying rates in the near term with an amplitude of −2 (+2) standard deviation of the IPO trend projected to amplify (weaken) the externally forced decrease in surface soil moisture by nearly 75% (60%). The findings highlight the need for the interplay between anthropogenic forcing and the natural variability of the IPO to be considered by policymakers in this climate-sensitive region.The interplay between anthropogenic forcing and internal variability associated with the Interdecadal Pacific Oscillation has exacerbated agricultural droughts over southern Central Asia since 1992, according to large ensemble simulations.

East Asia is greatly impacted by drought. North and southwest China are the regions with the highest drought frequency and maximum duration. At the interannual time scale, drought in the eastern part of East Asia is mainly dominated by two teleconnection patterns (i.e., the Pacific–Japan and Silk Road teleconnections). The former is forced by SST anomalies in the western North Pacific and the tropical Indian Ocean during El Niño decaying year summers. The precipitation anomaly features a meridional tripolar or sandwich pattern. The latter is forced by Indian monsoon heating and is a propagation of stationary Rossby waves along the Asian jet in the upper troposphere. It can significantly influence the precipitation over north China. Regarding the long-term trend, there exists an increasing drought trend over central parts of northern China and a decreasing tendency over northwestern China from the 1950s to the present. The increased drought in north China results from a weakened tendency of summer monsoons, which is mainly driven by the phase transition of the Pacific decadal oscillation. East Asian summer precipitation is poorly simulated and predicted by current state-of-the-art climate models. Encouragingly, the predictability of atmospheric circulation is high because of the forcing of ENSO and the associated teleconnection patterns. Under the SRES A1B scenario and doubled CO₂ simulations, most climate models project an increasing drought frequency and intensity over southeastern Asia. Nevertheless, uncertainties exist in the projections as a result of the selection of climate models and the choice of drought index.

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 western North Pacific Subtropical High (WNPSH) is a key circulation system controlling the summer monsoon and typhoon activities over the western Pacific, but future projections of its changes remain hugely uncertain. Here we find two leading modes that account for nearly 80% intermodel spread in its future projection under a high emission scenario. They are linked to a cold-tongue-like bias in the central-eastern tropical Pacific and a warm bias beneath the marine stratocumulus, respectively. Observational constraints using sea surface temperature patterns reduce the uncertainties by 45% and indicate a robust intensification of the WNPSH due to suppressed warming in the western Pacific and enhanced land-sea thermal contrast, leading to 28% more rainfall projected in East China and 36% less rainfall in Southeast Asia than suggested by the multi-model mean. The intensification of the WNPSH implies more future monsoon rainfall and heatwaves but less typhoon landfalls over East Asia. Model biases and internal variability are a cause for uncertainties in climate projections. Here, the authors show that 45% of projected uncertainty in the western Pacific Subtropical High can be reduced by correcting sea surface temperature biases in the equatorial Pacific and beneath marine stratocumulus clouds.

A stronger than global mean warming trend is projected over Central Asia in the coming century. Based on the historical simulations and projections under four combined scenarios of the Shared Socioeconomic Pathways and the Representative Concentration Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) provided by 15 models from the Sixth Phase of Coupled Model Intercomparison Project (CMIP6), we show a comprehensive picture of the future changes in precipitation over Central Asia under rapid warming and investigate possible mechanisms. At the end of the twenty-first century, robust increase of annual mean precipitation under all the scenarios is found (4.23 [2.60 to 7.36] %, 10.52 [5.05 to 13.36] %, 14.51 [8.11 to 16.91] %, 14.41 [9.58 to 21.26] % relative to the present-day for SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5, respectively). The response of precipitation to increasing global mean temperature shows similar spatial patterns for the four scenarios with stronger changes over Tianshan mountain and the northern part of Central Asia. Further analysis reveals a wetting trend in spring and a drying trend in summer in both the north of Central Asia (NCA) and south of Central Asia (SCA). The wetting trend in spring is balanced by the increase of evaporation, while the drying trend in summer is mainly contributed by the decrease of vertical moisture advection. The thermodynamic effects associated with humidity changes contribute to the drying trends in both the two domains, while the dynamic effects favor for the drying trend in NCA and offset the drying trend in SCA. The response of precipitation to increasing temperature results in enhanced seasonalities for SCA and NCA, and an advancing of the first peak from summer to spring in the NCA.

North China has undergone a severe drying trend since the 1950s, but whether this trend is natural variability or anthropogenic change remains unknown due to the short data length. This study extends the analysis of dry–wet changes in north China to 1900–2010 on the basis of self-calibrated Palmer drought severity index (PDSI) data. The ensemble empirical mode decomposition method is used to detect multidecadal variability. A transition from significant wetting to significant drying is detected around 1959/60. Approximately 70% of the drying trend during 1960–90 originates from 50–70-yr multidecadal variability related to Pacific decadal oscillation (PDO) phase changes. The PDSI in north China is significantly negatively correlated with the PDO index, particularly at the 50–70-yr time scale, and is also stable during 1900–2010. Composite differences between two positive PDO phases (1922–45 and 1977–2002) and one negative PDO phase (1946–76) for summer exhibit an anomalous Pacific–Japan/East Asian–Pacific patternlike teleconnection, which may develop locally in response to the PDO-associated warm sea surface temperature anomalies in the tropical Indo-Pacific Ocean and meridionally extends from the tropical western Pacific to north China along the East Asian coast. North China is dominated by an anomalous high pressure system at mid–low levels and an anticyclone at 850 hPa, which are favorable for dry conditions. In addition, a weakened land–sea thermal contrast in East Asia from a negative to a positive PDO phase also plays a role in the dry conditions in north China by weakening the East Asian summer monsoon.

The total column water vapor (TCWV) over the Tibetan Plateau (TP) is one important indicator of the Asian water tower, and the changes in the TCWV are vital to the climate and ecosystem in downstream regions. However, the observational data is insufficient to understand the changes in the TCWV due to the high elevation of the TP. Satellite and reanalysis data can be used as substitutes, but their quality needs to be evaluated. In this study, based on a homogenized radiosonde data set, a comprehensive evaluation of the TCWV over the TP derived from two satellite data sets (AIRS-only and AIRS/AMSU) and seven existing reanalysis data sets (MERRA, MERRA2, NCEP1, NCEP2, CFSR, ERA-I, JRA55) is performed in the context of the climatology, annual cycle and interannual variability. Both satellite data sets reasonably reproduce the characteristics of the TCWV over the TP. All reanalysis data sets perform well in reproducing the annual mean climatology of the TCWV over the TP (R = 0.99), except for NCEP1 (R = 0.96) and NCEP2 (R = 0.92). ERA-I is more reliable in capturing the spatial pattern of the annual cycle (R = 0.94), while NCEP1 shows the lowest skill (R = 0.72). JRA55 performs best in capturing the features of the interannual coherent variation (EOF1, R = 0.97). The skill-weighted ensemble mean of the reanalysis data performs better than the unweighted ensemble mean and most of the single reanalysis data sets. The evaluation provides essential information on both the strengths and weaknesses of the major satellite and reanalysis data sets in measuring the total column water vapor over the TP.

Eastern China experienced excessive Meiyu rainfall in the summer of 2020, with a long rainy season and frequent extreme rainfall events. Extreme rainfall occurred on daily to monthly time scales. In particular, persistent heavy rainfall events occurred; e.g., the maximum accumulated rainfall over four consecutive weeks (Rx28day) in the lower reaches of the Yangtze River was 94% greater than climatology, breaking the observational record since 1961. With ongoing anthropogenic climate change, it is vital to understand the anthropogenic influence on this extreme rainfall event and its driving mechanisms. In this study, based on multi-model simulations under different external forcings that participate in the Detection and Attribution Model Intercomparison Project (DAMIP) in the Coupled Model Intercomparison Project-phase 6 (CMIP6), we show that anthropogenic forcing has reduced the probability of the Rx28day extreme rainfall as that in observations in the lower reaches of the Yangtze River in 2020, by 46% (22–62%). Specifically, greenhouse gas (GHG) emissions have increased the probability by 44% as a result of atmospheric warming and moistening. However, this effect was offset by anthropogenic aerosols, which reduced the probability by 73% by reducing atmospheric moisture and weakening the East Asian summer monsoon circulation. With the continuous emissions of GHGs and reductions in aerosols in the future, similar persistent heavy rainfall events are projected to occur more frequently. A higher occurrence probability is expected under higher emission scenarios, which is estimated to be 4.6, 13.6 and 27.7 times that in the present day under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 emission scenarios, respectively, by the end of the 21st century. Thus, efficient mitigation measures will help to reduce the impacts related to extreme rainfall.

This paper evaluates sea surface temperature (SST) biases of coupled models participating in Coupled Model Intercomparison Project Phase 5 (CMIP5) and CMIP6. Overall, CMIP6 models perform better than CMIP5 ones in reproducing SST climatology, with lower multi‐model ensemble mean (MME) globally averaged absolute bias (1.17 vs. 1.31 K). MME bias in global mean annual SST shifts from cooling (−0.09 ± 0.52 K) to warming (0.23 ± 0.60 K). Regionally, in CMIP6 cooling biases over the Northwest Pacific and North Atlantic are reduced by 20% and 18%, while warming biases over the Northeast Pacific, Southeast Atlantic and Southern Ocean are increased by 25%, 16% and 107% respectively. These changes are mainly attributed to the combined effects from aggravated positive (or alleviated negative) bias in clear‐sky surface downward longwave radiation, and alleviated negative bias in cloud radiative effect, partially reduced by enhanced cooling bias in clear‐sky surface downward shortwave radiation. Plain Language Summary As the primary approach to projecting future climate change, state‐of‐the‐art climate models still suffer pronounced biases in climatological annual mean sea surface temperature (SST), such as cold biases over the Northwest Pacific and North Atlantic, and warm biases over the Northeast Pacific, Southeast Pacific, Southeast Atlantic and Southern Ocean. We have evaluated the changes in mean‐state SST biases between the Coupled Model Intercomparison Project Phase 5 (CMIP5) and CMIP6. CMIP6 models perform better in reproducing SST climatology with lower absolute bias, which is attributed to the process‐level improvement. Overall, annual global mean SST bias shifts from cold (−0.09 ± 0.52 K) to warm (0.23 ± 0.60 K), which is mainly due to the regionally alleviated cooling biases or aggravated warming biases. This warmer shift is contributed by the increased positive (or decreased negative) bias in clear‐sky surface downward longwave radiation and decreased negative bias in cloud radiative effect. Key Points Coupled Model Intercomparison Project Phase 6 (CMIP6) models perform better than CMIP5 ones, with significantly lower global‐mean absolute bias in annual sea surface temperature (SST) Global‐mean SST bias is with a warmer shift (+0.32 K) in CMIP6, with salient regional cold biases alleviated and warm biases aggravated Reduced cold bias in cloud radiative effect and positive change in bias in clear‐sky surface downward longwave together account for the shift

The atmospheric water vapor transport for summer precipitation over the southeastern Tibetan Plateau (hereafter TP) during 1979–2002 is examined by using five precipitation data sets and three reanalysis data sets. The multidata ensemble mean shows that under climate mean conditions, TP is a moisture sink in summer, having a net moisture convergence of 4 mm/day. The climatological water vapor transport from the southern boundary, which originates from the Indian Ocean and the Bay of Bengal, dominates the summer precipitation over the southeastern TP. It is estimated that the water vapor from the western boundary along the southern edge of the TP is about 32% of that from the southern boundary. The summer precipitation over the southeastern TP exhibits strong interannual variability, with a standard deviation of 1.3 mm/day, but no significant long‐term trend. The water vapor transport for the interannual variability of summer rainfall over the southeastern TP mainly comes from the western boundary of the TP, which is originally from lower latitudes. An excessive rainfall anomaly of 1 mm/day over the southeastern TP is associated with an anomalous water vapor input of 138 (104) kg/m/s from the western (southern) boundary. It is worth noting that the quantitative analysis in this study is determined by the setting of the domain. The interannual variability of summer precipitation over the southeastern TP is dominated by an anomalous anticyclone over the northern Indian subcontinent and the Bay of Bengal, which intensifies the water vapor transport along the southern edge of the TP and leads to more water vapor convergence over the southeastern TP, thus the excessive rainfall in the area. Key Points The climate mean water vapor transport is examined The interannual variability of water vapor transport is examined Compare the results by using mutiple data sets