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In recent years, various early warning signals of critical transition have been presented, such as autocorrelation at lag 1 [AR(1)], variance, the propagator based on detrended fluctuation analysis (DFA-propagator), and so on. Many studies have shown that the climate system has the characteristics of long-term memory (LTM). Will the LTM characteristics of the climate system change as it approaches possible critical transition points? In view of this, the present paper first studies whether the LTM of several folding (folded bifurcation) models changes consistently as they approach their critical points slowly by the rescaled range (R/S) analysis. The results of numerical experiments show that when the control parameters of the folding model are close to its critical threshold, the Hurst exponent H exhibits an almost monotonic increase (significance level α = 0.05). We compare the performance of R/S with the existing indicators, including AR(1), variance, and DFA-propagator, and find that R/S is a perfectly valid alternative. When there is no extra false noise, AR(1) and variance have good early warning effects. After the addition of extra Gaussian white noise of different intensities, the values of AR(1) and variance change significantly. As a result, the DFA-propagator based on AR(1) calibration also changed significantly. Compared with the other three indicators, the early warning effect of H has stronger ability to resist the interference of external false signals. To further verify the validity of increasing H, paleoclimate reconstruction of Cariaco Basin sediment core grayscale record with long trends filtered out is studied by R/S analysis. The other three early warning signals are calculated in the same way. The data contain a well-known abrupt climate change: the transition between the Younger Dryas (YD) and the Holocene. We find that approximately 300 years before this abrupt climate change occurred, before 11.7 kyr BP, the LTM exponents for Cariaco Basin deglacial grayscale data present an obvious increasing trend at a significant level of α = 0.05. Meanwhile, the variation trend of H and DFA-propagator is basically similar. This shows that increasing H by R/S analysis is an effective early warning signal, which indicates that a dynamic system is approaching its possible critical transition points; H is a completely valid alternative signal for AR(1) and DFA-propagator. The main conclusion of this paper is based on numerical experiments. The precise relationship between H and the stability of the underlying state approaching the transition needs to be further studied. [ABSTRACT FROM AUTHOR]

East Asian summer monsoon precipitation is projected to increase under greenhouse warming with strong intraseasonal variation. Using a 35-member CESM Large Ensemble and 30 CMIP6 models, this study reveals that in July and August, maximum rainfall changes in East Asia take place in the midlatitudes, influencing regions encompassing North and Northeast China, the Korean Peninsula, and Japan. The intensified precipitation is attributed to the combined effect of the thermodynamic and dynamic components. The former stems from the enriched low-level moisture, which peaks in continental East Asia in July and August, under global warming. The dynamic effect is due to the enhanced upward motion, associated with the enhanced southerlies throughout the troposphere over midlatitude East Asia. The southerlies also act to intensify the low-level monsoonal circulation, strengthening moisture transport from the tropical ocean to the midlatitudes. In addition to the mean-state changes, the precipitation interannual variability in this region also intensifies, partly due to the enhanced low-level moisture and partly associated with enhanced large-scale circulation anomalies, such as the northwestern Pacific anticyclone. The enhanced background precipitation, along with the intensified interannual variability, may lead to more rainy summers in a warmer climate, with instances where historically extreme precipitation events become more frequent, posing challenges for water resource management and agriculture in the region. [ABSTRACT FROM AUTHOR]

Of concern to Colorado River management, as operating guidelines post-2026 are being considered, is whether water resource recovery from low flows during 2000–20 is possible. Here, we analyze new simulations from phase 6 of the Coupled Model Intercomparison Project (CMIP6) to determine plausible climate impacts on Colorado River flows for 2026–50 when revised guidelines would operate. We constrain projected flows for Lees Ferry, the gauge through which 85% of the river flow passes, using its estimated sensitivity to meteorological variability together with CMIP6-projected precipitation and temperature changes. The critical importance of precipitation, especially its natural variability, is emphasized. Model projections indicate increased precipitation in the upper Colorado River basin due to climate change, which alone increases river flows by 5%–7% (relative to a 2000–20 climatology). Depending on the river's temperature sensitivity, this wet signal compensates for some, if not all, of the depleting effects of basin warming. Considerable internal decadal precipitation variability (∼5% of the climatological mean) is demonstrated, driving a greater range of plausible Colorado River flow changes for 2026–50 than previously surmised from treatment of temperature impacts alone: the overall precipitation-induced Lees Ferry flow changes span from −25% to +40%, contrasting with a range from −30% to −5% from expected warming effects only. Consequently, extreme low and high flows are more likely. Lees Ferry flow projections, conditioned on initial drought states akin to 2000–20, reveal substantial recovery odds for water resources, albeit with elevated risks of even further flow declines than in recent decades. Significance Statement: Increasing temperatures have led to concerns that Colorado River flows will be permanently reduced due to global warming. Here, we analyze precipitation, surface temperature, and streamflow (at Lees Ferry) in the upper Colorado River basin since 1895 revealing precipitation to be the largest contributor to runoff variability while temperature variability has been a much smaller contributor. New climate model projections indicate increased precipitation in the upper basin due to global warming, acting to increase river flows by 5%–7% during 2026–50. This wet signal compensates for some of the depleting effects from further basinwide warming. Critically, the large intrinsic variability in precipitation is demonstrated to yield a wider range of future Colorado River flows than previously foreseen based solely on considering temperature effects. [ABSTRACT FROM AUTHOR]

Recent research has shown that there is a projected increase in the frequency of strong positive Indian Ocean dipole (spIOD) events in terms of both sea surface temperature (SST) and precipitation. However, it is not clear whether the spIOD events defined by SST and precipitation, hereafter referred to as SST-spIOD and Pr-spIOD events, respectively, will increase at the same pace under greenhouse warming. Using climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and CMIP6 that can reasonably simulate the spIOD events, here we find that the occurrence of Pr-spIOD events increases much more than that of SST-spIOD events (+217% vs +77%) under the future high-emission scenario. The diverse response stems from a notably large increase in the spIOD events with strong rainfall but moderate SST anomalies (Pr-only spIOD), which is facilitated by a change in the local meridional Hadley circulation induced by land–sea thermal contrast in addition to the background mean-state SST warming. For the spIOD events with prominent anomalies in both rainfall and SST (concurrent spIOD), their occurrences are projected to increase, but their average SST amplitude is projected to weaken. The increased occurrence is associated with a westward-extended structural change induced by mean linear zonal advection feedbacks, while the weakened event-average SST amplitude results from a more stabilized atmosphere and coincides with the projected reduction in IOD SST skewness. Our results suggest that IOD-related mitigation strategies should consider the diverse responses of different kinds of spIOD events to greenhouse warming. [ABSTRACT FROM AUTHOR]

Accurately assessing cyclone intensity changes due to global warming is crucial for predicting and mitigating sequential hazards. This study develops a high-resolution, fully coupled air–sea model to investigate the impact of global warming on Supertyphoon Mangkhut (2018). A numerical sensitivity analysis is conducted using the pseudo–global warming (PGW) technique based on multiple global climate models (GCMs) from phase 6 of Coupled Model Intercomparison Project (CMIP6). Under ocean warming scenarios, the increasing average sea surface temperature (SST) by 2.26°, 2.44°, 3.45°, and 4.53°C results in reductions in the minimum sea level pressure by 9.2, 10.6, 15.7, and 19.4 hPa, respectively, compared to the original state of Typhoon Mangkhut. Rising SST increases the turbulent heat flux; to be specific, an average SST increase of 2.26°–4.53°C changes the turbulent heat flux into 177%–272% of the original value. Besides, stronger winds enhance SST cooling, including upwelling and entrainment, leading to an increase in the mixed layer depth (MLD). Tropical cyclone heat potential (TCHP) tends to be enhanced under the combined influences as the SST rises. An average increase in the SST of 2.26°, 2.44°, 3.45°, and 4.53°C leads to an increase in the TCHP of 9.94%, 9.85%, 14.67%, and 15.30%, respectively. However, future changes in atmospheric temperature and humidity will moderate typhoon intensification induced by ocean warming. Considering atmospheric conditions, the maximum wind speed decreases by approximately 10% compared to only considering ocean warming. Nevertheless, typhoon intensity is projected to strengthen under future climate change. Significance Statement: This study examines the role of global warming in typhoon intensity and the response of typhoon events to changes in the oceanic thermal structure. Sensitivity experiments considering future warming climates are conducted using a fully coupled air–sea numerical model. An average increase in sea surface temperature (SST) by 4.53°C can lead to a reduction in the minimum sea level pressure by 19.4 hPa. Ocean warming enhances oceanic mixing, potentially increasing the availability of heat energy for typhoon's development (i.e., an average increase in SST by 4.53°C leads to a 15.30% increase in heat energy). However, future changes in atmospheric temperature and humidity will moderate the intensification of typhoons induced by ocean warming. These results are expected to provide information for assessing the future changes in typhoon intensity under a warming climate, which is important for predicting and reducing sequential risks. [ABSTRACT FROM AUTHOR]

Here, we introduce the concept of "outdoor days" to describe how climate change can affect quality of life for different communities and individuals. An outdoor day is characterized by moderate temperature, neither too cold nor too hot, allowing most people to enjoy outdoor activities. The number of "outdoor days" is a nonlinear function of the daily surface air temperature. If the latter falls within a specific range describing assumed thermal comfort conditions, then we assign that day as an "outdoor day." Using this function, we describe climate change impacts on temperature differently, compared to other studies which often describe these impacts in terms of the linear averaging of daily surface air temperature. The introduction of this new concept offers another way for communicating how climate change may impact the quality of life for individuals who usually plan their outdoor activities based on how local weather conditions compare to their preferred levels of thermal comfort. Based on our analysis of regional variations in "outdoor days," we present observational and modeling evidence of a north–south disparity in climate change impacts. Under high-emission scenarios, CMIP5 and CMIP6 models project fewer "outdoor days" for people living in developing countries, primarily located in low-latitude regions. Meanwhile, developed countries in mid- and high-latitude regions could gain more "outdoor days," redistributed across seasons. Significance Statement: We introduce a novel concept: outdoor days, characterizing surface air temperature conditions that allow for outdoor activities, such as walking, jogging, and cycling, by most people. We project that under high-emission scenarios of anthropogenic greenhouse gases, a north–south disparity of climate change risk will be enhanced considerably toward the end of this century due to more frequent outdoor days in the wealthy Global North and less frequent outdoor days in the deprived Global South. [ABSTRACT FROM AUTHOR]

Using a range of Detection and Attribution Model Intercomparison Project (DAMIP) simulations from phase 6 of Coupled Model Intercomparison Project (CMIP6), we study the response of dynamic sea level (DSL) to external anthropogenic climate forcing [greenhouse gases (GHGs), aerosols, and stratospheric ozone] with a focus on the differences over the twentieth and twenty-first century. In the second half of the twentieth century, the DSL nonuniformity in the Northern Hemisphere (NH) was relatively small due to a cancellation between the effects of increasing GHGs and aerosols. In contrast, the DSL signal in the Southern Hemisphere (SH) over this period was large because stratospheric ozone depletion reinforced the effects of increasing GHGs. In the twenty-first century, the DSL response has been intensified in the NH because the warming effects of diminishing aerosols have acted to reinforce the effects of increasing GHGs. Meanwhile, the distribution of SH DSL has also become uneven although stratospheric ozone recovery has partially offset the effects of rising GHGs. Using a global ocean circulation model, we decompose the changes in the twenty-first century DSL into distinct responses to surface forcings including sea surface temperature, salinity, and wind stress. Our results show that the dipole-like pattern of DSL in the North Pacific can be attributed largely to sea surface warming, while the dipole-like pattern in the North Atlantic is attributed to subpolar surface salinity freshening. The belted pattern of DSL changes in the Southern Ocean is induced by both surface warming and intensifying/poleward-shifting westerly winds. [ABSTRACT FROM AUTHOR]

Heat lows are key features of subtropical climates and monsoon systems. In southern Africa, they are pivotal to understanding divergent climate change projections, in particular the veracity of future rainfall decline. Compared to other heat lows, including in West Africa and Australia, the southern African heat low remains poorly documented. Here, we analyze the diurnal cycle, seasonal variability, and trends of the heat low in reanalysis data. In ERA5, 462 strong heat low days are detected between September and March from 1990 to 2019, equating to 7.3% of days sampled. These events feature ascent (exceeding −0.2 Pa s−1) at low levels (strongest between 800 and 600 hPa) and subsidence aloft, generating low-level cyclonic flow with anticyclonic flow above. This flow exhibits strong diurnal variability, with peak windspeeds between 0600 and 0900 UTC and maximum ascent at ∼2300 UTC. Heat lows form preferentially over Angola in September (∼14°S) and October (15°–20°S), and in Namibia from November to March (∼20°–26°S). Strongest ascent occurs over areas of high elevation. Finally, we show a rapidly increasing frequency of strong heat low days, with a 175% increase between 1960–89 and 1990–2019. The greatest increase (459%) has occurred in the early summer months of September and October, consistent with projections of delayed rainfall onset. Strikingly, more strong heat lows are detected in the most recent 5 years of analysis (2014–19) than in the 30-yr period from 1960 to 1989. These results suggest the heat low is an important feature in determining drying trends over southern Africa and is a vital indicator of climate model accuracy. Significance Statement: This work documents the heat low that forms in southern Africa in the lowest levels of the atmosphere. The feature is present during austral summer (from September to March) and is associated with below average rainfall across much of the subcontinent. The frequency of strong heat lows has rapidly increased in line with regional amplified warming trends. The heat low is identified as an important control on circulation and precipitation patterns and changes in the frequency or intensity of the feature in the future are likely to influence the strength of declining rainfall trends across southern Africa. [ABSTRACT FROM AUTHOR]

Climate models generally predict a poleward shift of the midlatitude circulation in response to climate change induced by increased greenhouse gas concentration, but the intermodel spread of the eddy-driven jet shift is large and poorly understood. Recent studies point to the significance of midlatitude midtropospheric diabatic heating for the intermodel spread in the jet latitude. To examine the role of diabatic heating in the jet response to climate change, a series of simulations are performed using an idealized aquaplanet model. It is found that both increased CO2 concentration and increased saturation vapor pressure induce a similar warming response, leading to a poleward and upward shift of the midlatitude circulation. An exception to this poleward shift is found for a certain range of temperatures, where the eddy-driven jet shifts equatorward, while the latitude of the eddy heat flux remains essentially unchanged. This equatorward jet shift is explained by the connection between the zonal-mean momentum and heat budgets: increased diabatic heating in the midlatitude midtroposphere balances the cooling by the Ferrel cell ascending branch, enabling an equatorward shift of the Ferrel cell streamfunction and eddy-driven jet, while the latitude of the eddy heat flux remains unchanged. The equatorward jet shift and the strengthening of the midlatitude diabatic heating are found to be sensitive to the model resolution. The implications of these results for a potential reduction in the jet shift uncertainty through the improvement of convective parameterizations are discussed. Significance Statement: The latitude of the eddy-driven jet displays considerable variation in climate models, and the factors influencing this variability are poorly understood. This work connects the strength of midlatitude diabatic heating to the structure of the midlatitude circulation and the eddy-driven jet latitude. The direction of the eddy-driven jet shift in response to climate change is found to depend on the diabatic heating response, which in turn depends on the parameterized convective heating. These results highlight the role of convective parameterizations in the representation of the midlatitude circulation in climate models. Additionally, the results imply that the eddy-driven jet shift cannot be explained solely based on the storm-track response to climate change, in contrast with previously suggested explanations. [ABSTRACT FROM AUTHOR]

Indian Ocean (IO) stratification has important effects on the air–sea interaction, ocean dynamics, and ecology. It is, therefore, of significance to investigate the changes in IO stratification. In this study, we use ensemble empirical mode decomposition (EEMD) to extract the nonlinear long-term trend in the upper IO stratification quantified by potential energy anomalies. The results show that the strengthening of the stratification is spatially and temporally nonuniform. Specifically, the trend of stratification intensified gradually before 1996, but accelerated rapidly after 1996. Temperature and salinity changes play a crucial role in the fast enhancement of stratification and its regional differences. Temperature variations dominate the stratification trend in ∼90% of the IO area, while the contributions of salinity changes are mainly in the southeast Indian Ocean (SEIO). Vertically, the rapid enhancement of stratification is caused by the trend of temperature and salt in the upper 400 m. We further perform temperature budget analysis and find that the warming trend in the upper 400 m south of the IO is mainly modulated by vertical advection and meridional advection, while the warming in the north of the IO is mainly induced by air–sea heat fluxes. Salinity budget analysis shows that ocean advection has played a primary role in modulating SEIO salinity over the past 20 years. [ABSTRACT FROM AUTHOR]

Land surface air temperatures (LSAT) inferred from weather station data differ among major research groups. The estimate by NOAA's monthly Global Historical Climatology Network (GHCNm) averages 0.02°C cooler between 1880 and 1940 than Berkeley Earth's and 0.14°C cooler than the Climate Research Unit estimates. Such systematic offsets can arise from differences in how poorly documented changes in measurement characteristics are detected and adjusted. Building upon an existing pairwise homogenization algorithm used in generating the fourth version of NOAA's GHCNm(V4), PHA0, we propose two revisions to account for autocorrelation in climate variables. One version, PHA1, makes minimal modification to PHA0 by extending the threshold used in breakpoint detection to be a function of LSAT autocorrelation. The other version, PHA2, uses penalized likelihood to detect breakpoints through optimizing a model-selection problem globally. To facilitate efficient optimization for series with more than 1000 time steps, a multiparent genetic algorithm is proposed for PHA2. Tests on synthetic data generated by adding breakpoints to CMIP6 simulations and realizations from a Gaussian process indicate that PHA1 and PHA2 both similarly outperform PHA0 in recovering accurate climatic trends. Applied to unhomogenized GHCNmV4, both revised algorithms detect breakpoints that correspond with available station metadata. Uncertainties are estimated by perturbing algorithmic parameters, and an ensemble is constructed by pooling 50 PHA1- and 50 PHA2-based members. The continental-mean warming in this new ensemble is consistent with that of Berkeley Earth, despite using different homogenization approaches. Relative to unhomogenized data, our homogenization increases the 1880–2022 trend by 0.16 [0.12, 0.19]°C century−1 (95% confidence interval), leading to continental-mean warming of 1.65 [1.62, 1.69]°C over 2010–22 relative to 1880–1900. Significance Statement: Accurately correcting for systematic errors in observational records of land surface air temperature (LSAT) is critical for quantifying historical warming. Existing LSAT estimates are subject to systematic offsets associated with processes including changes in instrumentation and station movement. This study improves a pairwise homogenization algorithm by accounting for the fact that climate signals are correlated over time. The revised algorithms outperform the original in identifying discontinuities and recovering accurate warming trends. Applied to monthly station temperatures, the revised algorithms adjust trends in continental mean LSAT since the 1880s to be 0.16°C century−1 greater relative to raw data. Our estimate is most consistent with that from Berkeley Earth and indicates lesser and greater warming than estimates from NOAA and the Met Office, respectively. [ABSTRACT FROM AUTHOR]

A main source of regional climate change uncertainty is the large disparity across models in simulating the atmospheric circulation response to global warming. Using the latest suite of global climate models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6), a storyline approach is adopted to derive physically plausible scenarios of Antarctic climate change for 2070–99, according to Shared Socioeconomic Pathway SSP5-8.5. These storylines correspond to differences in the simulated amount of seasonal sea ice loss and either (i) the delay in the summertime stratospheric polar vortex (SPV) breakdown or (ii) wintertime SPV strengthening, which together constitute robust drivers of the response pattern to future climate change. Such changes combined are known to exert a strong control over the Southern Hemisphere midlatitude jet stream, which we quantify as collectively explaining up to 70% of the variance in jet response in summer and 35% in winter. For summer, the expected strengthening and displacement of the tropospheric jet stream varies between a ∼1 and 2 m s−1 increase and ∼2°–4° poleward shift, respectively, across storylines. In both seasons, a larger strengthening of the jet is correlated with less Antarctic warming. By contrast, the response in precipitation is more consistent but still strongly attenuated by large-scale dynamics. We find that an increase in high-latitude precipitation around Antarctica is more pronounced for storylines characterized by a greater poleward jet shift, particularly in summer. Our results highlight the usefulness of the storyline approach in illustrating model uncertainty and understanding the processes that determine the spread in projected Antarctic regional climate response. Significance Statement: Uncertainty in future climate predictions for the Antarctic is dominated by the unknown response of the large-scale (global) atmospheric circulation. In characterizing such uncertainty, plausible outcomes of climate response (storylines) are generated from the organization of model projections according to the amount of simulated seasonal sea ice loss and the delay in summertime breakdown/winter strengthening of the stratospheric westerly circulation (polar vortex). The intensity and location of the tropospheric jet stream is strongly dependent on both factors, which strongly influences the near-surface climate response over Antarctica. We find that the simulated amount that Antarctic air temperatures increase by in the future (to the end of the century) is intrinsically related to the projected intensification of the Southern Hemisphere tropospheric jet, varying by a factor of 2 or more across storylines for summer. Storylines with greater jet strengthening are associated with less Antarctic warming (reduced poleward advection of air masses from lower latitudes). Similar differences are found for changes in jet position, which we note has a much stronger control on mid- to high-latitude precipitation response. This includes both an enhanced wetting response around Antarctica and drying response farther equatorward, for storylines characterized by a greater poleward jet shift. [ABSTRACT FROM AUTHOR]

Assessing how global warming affects tropical cyclones (TC) is immensely important for climate change adaptation and hazard mitigation. However, projected intensity and size change can vary greatly among different individual storms, even under the same forcing in pseudo–global warming (PGW) experiments. Here we hypothesize that these variations are related to the historical environment in which each TC was embedded. Twenty-five TCs in the South China Sea (SCS) region were simulated using the Weather Research and Forecasting (WRF) Model. Their changes in the near (2036–65) and far future (2075–99) following the representative concentration pathways 8.5 (RCP8.5) and 4.5 (RCP4.5) under phase 5 of the Coupled Model Intercomparison Project (CMIP5) were investigated by the PGW technique. The mean changes in TC intensity and gale-force wind radius (R17) in the SCS were +6.4% and +1.5% for a 2°C warming, respectively. Multiple linear regression and stepwise regression analysis revealed that storm intensity variations were positively correlated with historical sea surface temperature and negatively with outer (i.e., outside the TC's R17) atmospheric instability, while the R17 variations correlated positively with outer midtropospheric relative humidity (RH) and surface outer wind speed (OWS). Ertel potential vorticity (EPV) diagnostics further showed a moister SCS background can cause stronger diabatic heating and EPV production at the spiral rainbands under PGW, which increases R17. Additionally, stronger background absolute angular momentum (AAM) promoted stronger AAM influx, leading to larger R17. Implications were drawn to explain the uncertainties in projected TC intensity and size due to natural variability. Significance Statement: Changes in the intensity and size of individual tropical cyclones in future climates are highly variable. This study aims to understand the environmental factors influencing these variations. We selected 25 storms that entered the South China Sea region and modeled them in both present and future climates. The mean intensity and size were projected to increase by 6.4% and 1.5% for a 2°C warming, respectively. We found that tropical cyclones embedded in historically warmer oceans and more stable atmospheres intensified more than the others, while historically wetter and windier environments promoted larger size growth. Our results suggest that certain tropical cyclones can exhibit a greater increase in intensity and size in a warmer climate under favorable environmental conditions. [ABSTRACT FROM AUTHOR]

Weighting models according to their performance has been used to produce multimodel climate change projections. But the added value of model weighting for future projection is not always examined. Here we apply an imperfect model framework to evaluate the added value of model weighting in projecting summer temperature changes over China. Members of large-ensemble simulations by three climate models of different climate sensitivities are used as pseudo-observations for the past and the future. Performance of the models participating in the phase 6 of the Coupled Model Intercomparison Project (CMIP6) are evaluated against the pseudo-observations based on simulated historical climatology and trends in global, regional, and local temperatures to determine the model weights for future projection. The weighted projections are then compared with the pseudo-observations in the future period. We find that regional trend as a metric of model performance yields generally better skill for future projection, while past climatology as performance metric does not lead to a significant improvement to projection. Trend at the grid-box scale is also not a good performance indicator as small-scale trend is highly uncertain. For the model weighting to be effective, the metric for evaluating the model's performance must be relatable to future changes, with the response signal separable from internal variability. Projected summer warming based on model weighting is similar to that of unweighted projection but the 5th–95th-percentile uncertainty range of the weighted projection is 38% smaller with the reduction mainly in the upper bound, with the largest reduction appearing in southeast China. [ABSTRACT FROM AUTHOR]

In China, the topography, climate, ecology, hydrology, and human environment vary greatly from southeast to northwest, and a typical natural and social environmental transition zone (i.e., comprehensive transition zone) exists near the "Hu Huanyong line," which is a famous demographic dividing line in China, known as the Hu zone. Dry and wet climate changes in the Hu zone can have a significant impact on terrestrial ecosystems and hydrological conditions, ultimately affecting human–land relations. However, there is still a lack of clear understanding of environmental changes in the context of climate change in the Hu zone. Here, a quantitative analysis of climate change and its impacts on terrestrial hydrology and ecosystems from 1951 to 2020 is presented. The results showed that there exists a significant drying trend in the Hu zone and a dramatic decrease in terrestrial water storage (TWS), indicating that the environment has become worse. Conversely, from the perspective of significant greening, the environment has improved. This contradiction is mainly due to climate change dominating the depletion of TWS, while the increase in vegetation greenness is more driven by human activities including agricultural management and ecological restoration, offsetting to some extent the negative impact of water scarcity on vegetation growth. Significance Statement: The Hu zone is a transition zone between southeast and northwest China, which is a sensitive area under climate change as well as key region for coordinated development. The purpose of this study is to reveal the long-term climate change in the Hu zone and its impacts on hydrology and ecology. Our results indicate a significant drying trend in this zone over the last 70 years, which led to a substantial reduction in water storage. However, the vegetation coverage increased due to human activities. This study provides guidance for agricultural structure adjustment and ecological protection in transition zones. Future research should focus more on the assessment and risk management of dry/wet changes in climate transition areas around the world. [ABSTRACT FROM AUTHOR]

El Niño–Southern Oscillation (ENSO) is often characterized through the use of sea surface temperature (SST) departures from their climatological values, as in the Niño-3.4 index. However, this approach is problematic in a changing climate when the climatology itself is varying. To address this issue, van Oldenborgh et al. proposed a relative Niño-3.4 SST index, which subtracts the tropical mean SST anomaly from the Niño-3.4 index and multiplies by a scaling factor. We extend their work by providing a simplified calculation procedure for the scaling factor, and confirm that the relative index demonstrates reduced sensitivity to climate change and multidecadal variability. In particular, we show in three observational SST datasets that the relative index provides a more consistent classification of historical El Niño and La Niña oceanic conditions that is more robust across climatological periods compared to the nonrelative index. Forecast skill of the relative Niño-3.4 index in the North American Multimodel Ensemble (NMME) and ACCESS-S2 is slightly reduced for targets during the first half of the year because subtracting the tropical mean removes a source of additional skill. For targets in the second half of the year, the relative and nonrelative indices are equally skillful. Observed ENSO teleconnections in 200-hPa geopotential height and precipitation during key seasons are sharper and explain more variability over Australia and the contiguous United States when computed with the relative index. Overall, the relative Niño-3.4 index provides a more robust option for real-time monitoring and forecasting ENSO in a changing climate. Significance Statement: The goal of this study is to further explore a relative sea surface temperature index for monitoring and prediction of El Niño–Southern Oscillation. Sea surface temperature indices are typically computed as a difference from a 30-yr climatological average, and El Niño and La Niña events occur when values exceed a certain threshold. This method is suitable when the climate is stationary. However, because of climate change and other lower-frequency variations, historical El Niño and La Niña events are reclassified depending on which climatological period is selected. A relative index is investigated to ameliorate this problem. [ABSTRACT FROM AUTHOR]

Arctic Ocean warming and sea ice loss are closely linked to increased ocean heat transport (OHT) into the Arctic and changes in surface heat fluxes. To quantitatively assess their respective roles, we use the 100-member Community Earth System Model, version 2 (CESM2), Large Ensemble over the 1920–2100 period. We first examine the Arctic Ocean warming in a heat budget framework by calculating the contributions from heat exchanges with atmosphere and sea ice and OHT across the Arctic Ocean gateways. Then we quantify how much anomalous heat from the ocean directly translates to sea ice loss and how much is lost to the atmosphere. We find that Arctic Ocean warming is driven primarily by increased OHT through the Barents Sea Opening, with additional contributions from the Fram Strait and Bering Strait OHTs. These OHT changes are driven mainly by warmer inflowing water rather than changes in volume transports across the gateways. The Arctic Ocean warming driven by OHT is partially damped by increased heat loss through the sea surface. Although absorbed shortwave radiation increases due to reduced surface albedo, this increase is compensated by increasing upwelling longwave radiation and latent heat loss. We also explicitly calculate the contributions of ocean–ice and atmosphere–ice heat fluxes to sea ice heat budget changes. Throughout the entire twentieth century as well as the early twenty-first century, the atmosphere is the main contributor to ice heat gain in summer, though the ocean's role is not negligible. Over time, the ocean progressively becomes the main heat source for the ice as the ocean warms. Significance Statement: Arctic Ocean warming and sea ice loss are closely linked to increased ocean heat transport (OHT) into the Arctic and changes in surface heat fluxes. Here we use 100 simulations from the same climate model to analyze future warming and sea ice loss. We find that Arctic Ocean warming is primarily driven by increased OHT through the Barents Sea Opening, though the Fram and Bering Straits are also important. This increased OHT is primarily due to warmer inflowing water rather than changing ocean currents. This ocean heat gain is partially compensated by heat loss through the sea surface. During the twentieth century and early twenty-first century, sea ice loss is mainly linked to heat transferred from the atmosphere; however, over time, the ocean progressively becomes the most important contributor. [ABSTRACT FROM AUTHOR]

The surface and air temperature gradient (TS00 − Tair) drives the development of the convective boundary layer and the occurrence of clouds and precipitation. However, its variability is still poorly understood due to the lack of high-quality observations. This study fills in this gap by investigating the diurnal to decadal variability in TS00 − Tair from 2002 to 2022 based on hourly observations collected at over 100 stations of the U.S. Climate Reference Network. It is found that TS00 − Tair reaches its maximum at noon with an average of 6.85°C over the contiguous United States, which decreases to 4.28°C when the soil moisture exceeds 30%. The daily minimum of TS00 − Tair has an average of −2.08°C, which generally occurs in the early evening but is postponed as the cloud fraction decreases. Moreover, while existing studies have used the near-surface soil temperature, such as the 5-cm soil temperature (TS05), to calculate TS05 − Tair, we find that TS00 − Tair and TS05 − Tair have opposite diurnal cycles, and their amplitudes differed drastically. The daily minimum of TS00 − Tair has a significant decreasing trend (−0.50° ± 0.007°C decade−1) from 2002 to 2022 due to Tair increasing at a higher rate than TS00 during the nighttime. The occurrence frequency of near-surface stable conditions (TS00 − Tair < 0) increases significantly, and the frequency of unstable conditions (TS00 − Tair > 0) decreases notably throughout the year except for winter. When it is stable, the magnitude of TS00 − Tair tends to decrease while the TS00 − Tair tends to increase when it is unstable, which is consistent with the drying condition caused by the precipitation deficit. This study provides the first observational evidence on how TS00 − Tair responds to warming. Significance Statement: The impact of global warming on surface-air temperature gradients is a crucial scientific issue that needs to be addressed. These gradients determine changes in cloud and precipitation, affecting water resources. However, traditional surface temperature measurements from weather stations are of high uncertainty due to direct exposure to the insolation. Satellite retrieval of surface temperature is limited by the availability of clear sky conditions, with low accuracy for temperature gradient calculations. Despite their importance, high-accuracy data of land surface temperature are still lacking. To address this issue, the U.S. Climate Reference Network (USCRN) uses infrared radiometers to continuously monitor surface temperature with high accuracy and sampling frequency. This study reports on surface-air temperature gradients at more than 100 U.S. stations, providing insight into diurnal to decadal variability over the contiguous United States. The study also highlights the significant difference between the land surface temperature–air temperature gradient and soil temperature–air temperature gradient. [ABSTRACT FROM AUTHOR]

The zonal sea surface temperature (SST) gradient across the tropical Pacific is a pacemaker of the variable rates of global warming. In both historical simulations and future projections, the current state-of-the-art climate models show evident spread in the changes of zonal SST gradient, but the reasons remain unknown. Here, we quantify the contributions of internal variability and model spread to the uncertainty of zonal SST gradient changes by analyzing 342 realizations from CMIP5 and CMIP6 models and several sets of large-ensemble simulations. We found that the internal variability dominates the total uncertainty at multidecadal time scales (∼31-yr trends). Although the ratio of internal uncertainty to the total uncertainty declines along with higher emission of greenhouse gases under global warming, it is still over 80% at the multidecadal time scales in the future. The Pacific decadal oscillation is identified as the key internal mode responsible for the multidecadal uncertainty. For the future projections at centurial time scales, the uncertainty of zonal SST gradient changes is mainly from the intermodel spread in response to external forcing, accounting for about 70% of the uncertainty based on the difference between 2070–99 and 1970–99. The model spread in the cloud–shortwave radiation–SST feedback over the tropical Pacific is important in the uncertainty of zonal SST gradient changes. In particular, the intensity of negative convective cloud feedback in the western Pacific dominates the spread in CMIP5 models, while the intensity of stratocumulus cloud feedback over the southeastern Pacific is the primary process influencing the uncertainty in CMIP6 models. [ABSTRACT FROM AUTHOR]

Future Arctic sea ice loss has a known impact on Arctic amplification (AA) and mean atmospheric circulation. Furthermore, several studies have shown it leads to a decreased variance in temperature over North America. In this study, we analyze results from two fully coupled Community Earth System Model (CESM) Whole Atmosphere Community Climate Model (WACCM4) simulations with sea ice nudged to either the ensemble mean of WACCM historical runs averaged over the 1980–99 period for the control (CTL) or projected RCP8.5 values over the 2080–99 period for the experiment (EXP). Dominant large-scale meteorological patterns (LSMPs) are then identified using self-organizing maps applied to winter daily 500-hPa geopotential height anomalies ( Z 500 ′ ) over North America. We investigate how sea ice loss (EXP − CTL) impacts the frequency of these LSMPs and, through composite analysis, the sensible weather associated with them. We find differences in LSMP frequency but no change in residency time, indicating there is no stagnation of the flow with sea ice loss. Sea ice loss also acts to de-amplify and/or shift the Z 500 ′ that characterize these LSMPs and their associated anomalies in potential temperature at 850 hPa. Impacts on precipitation anomalies are more localized and consistent with changes in anomalous sea level pressure. With this LSMP framework we provide new mechanistic insights, demonstrating a role for thermodynamic, dynamic, and diabatic processes in sea ice impacts on atmospheric variability. Understanding these processes from a synoptic perspective is critical as some LSMPs play an outsized role in producing the mean response to Arctic sea ice loss. Significance Statement: The goal of this study is to understand how future Arctic sea ice loss might impact daily weather patterns over North America. We use a global climate model to produce one set of simulations where sea ice is similar to present conditions and another that represents conditions at the end of the twenty-first century. Daily patterns in large-scale circulation at roughly 5.5 km in altitude are then identified using a machine learning method. We find that sea ice loss tends to de-amplify these patterns and their associated impacts on temperature nearer the surface. Our methodology allows us to probe more deeply into the mechanisms responsible for these changes, which provides a new way to understand how sea ice loss can impact the daily weather we experience. [ABSTRACT FROM AUTHOR]

The mid-Pliocene (approximately 3.3–3.0 Ma) was one of the past geological warm periods. Since this past warmer climate was in many respects comparable to near future warming projections, how the regional monsoonal rainfall changed during the mid-Pliocene is an important scientific and socioeconomic concern. Based on phase 2 of the Pliocene Model Intercomparison Project (PlioMIP2), this work examines the simulated changes of Sahel summer rainfall during the mid-Pliocene. The results show the considerable intermodel uncertainty of the simulated mid-Pliocene Sahel rainfall changes in the PlioMIP2 multimodel ensemble, which is due to the uncertainties of both the simulated dynamic and thermodynamic responses to this past warmer climate. In particular, we find that the intermodel spread in the simulated northern North American warming is a major source of the uncertainty of the mid-Pliocene Sahel summer rainfall changes through two processes. One is a direct dynamic process: a stronger warming over northern North America could enhance the meridional temperature gradient between the extratropical and tropical regions, inducing an interhemisphere energy imbalance of the atmosphere. This could lead to a northward shift of the intertropical convergence zone, strengthening the Western African summer monsoon (WASM) circulation and Sahel summer rainfall. Another is an indirect thermodynamic process: the strengthened WASM circulation could further induce anomalous moisture convergence over the Sahel region, increasing local atmospheric moisture at the low-level troposphere, in favor of a wetter Sahel. Our results suggest that an improved warming simulation over northern North America is essential for the hydrological cycle simulation around the Sahel in the mid-Pliocene warmer climate. Significance Statement: The Sahel summer rainfall change in a global warmer climate is a widespread scientific and socioeconomic issue because of its important impacts on regional agriculture, ecosystems, food security, water resources, and even cultural environment. However, the present study identifies a nonnegligible intermodel uncertainty of the simulated Sahel rainfall changes during the mid-Pliocene (one of the most recent geological warm periods in Earth's history) in the Pliocene Model Intercomparison Project phase 2 (PlioMIP2) multimodel ensemble. In particular, such an intermodel uncertainty of the simulated Sahel rainfall changes during the mid-Pliocene is attributed to that of the simulated northern North America warming via both the direct dynamic process and the indirect thermodynamic process. This is quite different from the uncertainty source of near-future projections of Sahel summer rainfall changes. The present results improve our understanding of the underlying physics of the hydrological cycle change around the Sahel region in the mid-Pliocene warmer climate, with implications for the future projections of regional monsoonal rainfall. [ABSTRACT FROM AUTHOR]

Several recent studies have highlighted differences in simulated properties of El Niño–Southern Oscillation (ENSO) under transient and equilibrium responses to increasing CO2. However, the reasons behind these disparate responses and the extent to which they are robust to different scales of CO2 forcing remain unclear. In this study, we adopt a climate system model with reduced SST bias in the eastern tropical Pacific and incrementally apply abrupt increases in CO2, analyzing outputs after each simulation reaches quasi-equilibrium with the imposed forcing. The results suggest that ENSO activity under quasi-equilibrium first increases and then decreases with increasing CO2, peaking in simulations with CO2 concentrations similar to the present day. Bjerknes–Jin stability analysis indicates that changes in the ENSO growth rate result primarily from changes in the thermocline feedback and thermodynamic damping terms. While thermodynamic damping increases monotonically with increasing CO2, the positive thermocline feedback varies within the range of internal variability up to twice the preindustrial value of CO2 and then weakens sharply with further increases. The mechanisms behind these changes include weaker mean ocean upwelling and weaker dynamical coupling between the atmosphere and subsurface ocean associated with substantial near-surface freshening at higher levels of CO2. These changes steepen the thermodynamic barrier to mixing between the surface and subsurface, weakening the east–west temperature gradient in the mean state and suppressing variability in the cold tongue. Analysis of similar model simulations from the Coupled Model Intercomparison Project (CMIP6) archive indicates that changes in the Bjerknes–Jin stability index are robust but do not establish a consensus as to the mechanisms behind them. Significance Statement: This study investigates how El Niño–Southern Oscillation changes with increasing CO2 forcing by using a global model with improved tropical Pacific climate. The simulations roughly correspond to scenarios in which emissions are reduced to maintain CO2 concentrations at near-constant values over a long period, with levels ranging from about 2/3 to more than 5 times the present-day concentration. Analysis of these simulations suggests that ENSO activity is strongest when CO2 concentrations are similar to the present-day and becomes substantially weaker when CO2 is more than double its present-day value. Reduced ENSO activity with further increases in CO2 is caused by weaker interactions between the atmosphere and the subsurface ocean. Both the amplitude of warm (El Niño) events and the occurrence frequency of warm and cold (La Niña) events decrease as ENSO events become first more difficult to grow and then more difficult to trigger with increasing CO2. [ABSTRACT FROM AUTHOR]

Most of the globe has experienced significant warming trends that have been attributed to anthropogenic climate change. However, these rates of warming are also influenced by short-term climate fluctuations driven by atmospheric circulation dynamics, resulting in inconsistent trend magnitudes in both time and space. This research evaluated winter (December-February) temperature trends over 1950-2020 at 91 climate stations across British Columbia (BC), Alberta (AB), and Saskatchewan (SK), Canada, and determined the components attributed to thermodynamic and dynamic (atmospheric circulation) factors. A synoptic climatological approach was used to classify atmospheric circulation patterns in the midtroposphere, relate those patterns to surface temperature, and evaluate changes in frequency. Moderate to high temperature increases over 71 years were found for most of the region, averaging 3.18C in southern SK to 4.1℃ in central-northern AB, and a maximum of 5.8℃ in northern BC. Low to moderate increases were found for southern BC, averaging 1.2℃. Changes in atmospheric circulation accounted for 29% and 31% of observed temperature changes in central-northern BC and AB, respectively. Dynamic factors were a moderate driver in southern AB (18%) and central-northern SK (13%), and low in southern SK (5%). Negative dynamic contributions in southern BC (-6%), suggest that atmospheric circulation changes counteracted thermodynamically driven temperature changes. Results were consistent with trend analyses, indicating this method is well suited for trend detection and identification of thermodynamic and dynamic drivers. Results of this research improve our understanding of the magnitude of winter temperature changes critical for informing adaptation and climate-related policy decisions. [ABSTRACT FROM AUTHOR]

The dynamic and thermodynamic mechanisms that link retreating sea ice to increased Arctic cloud amount and cloud water content are unclear. Using the fifth generation of the ECMWF Reanalysis (ERA5), the long-term changes between years 1950-79 and 1990-2019 in Arctic clouds are estimated along with their relationship to sea ice loss. A comparison of ERA5 to CERES satellite cloud fractions reveals that ERA5 simulates the seasonal cycle, variations, and changes of cloud fraction well over water surfaces during 2001-20. This suggests that ERA5 may reliably represent the cloud response to sea ice loss because melting sea ice exposes more water surfaces in the Arctic. Increases in ERA5 Arctic cloud fraction and water content are largest during October-March from ~950 to 700 hPa over areas with significant (>15%) sea ice loss. Further, regions with significant sea ice loss experience higher convective available potential energy (~2-2.75 J kg-1), planetary boundary layer height (~120-200 m), and near-surface specific humidity (~0.25-0.40 g kg-1) and a greater reduction of the lower-tropospheric temperature inversion (~3°-4℃) than regions with small (<15%) sea ice loss in autumn and winter. Areas with significant sea ice loss also show strengthened upward motion between 1000 and 700 hPa, enhanced horizontal convergence (divergence) of air, and decreased (increased) relative humidity from 1000 to 950 hPa (950-700 hPa) during the cold season. Analyses of moisture divergence, evaporation minus precipitation, and meridional moisture flux fields suggest that increased local surface water fluxes, rather than atmospheric motions, provide a key source of moisture for increased Arctic clouds over newly exposed water surfaces during October-March. [ABSTRACT FROM AUTHOR]

The impacts of tropical sea surface temperature (SST) changes on the Madden-Julian oscillation (MJO) are investigated using the large-ensemble simulation from the Community Earth System Model version 2 (CESM2-LE) under the shared socioeconomic pathway (SSP370 scenario). Three SST change patterns are featured, distinguished by the zonal gradient of the change in the equatorial Pacific warming. MJO characteristics and its teleconnections responses are composited for the clusters, and their relationships to the zonal SST gradient changes are examined. Results show that the anomalously strong El Niño-like SST change pattern significantly intensifies the MJO amplitude and enhances its eastward extension compared to the anomalously weak El Niño-like SST change pattern. These changes in MJO amplitude are further interpreted through the α framework. We also found no statistically different extratropical geopotential height responses to MJO between the three SST warming patterns, possibly due to strong internal climate variability. Changes in Rossby wave source between clusters also show a weak relationship with the MJO teleconnections. Our results highlight the importance of Indo-Pacific zonal SST gradient changes on the changes of MJO but limited impacts on MJO teleconnections to the midlatitudes. [ABSTRACT FROM AUTHOR]

Twenty years of satellite-based cloud and radiation observations allow us to examine the observed cloud radiative effect (CRE) feedback (i.e., CRE change per unit change in global mean surface temperature). By employing a decomposition method to separate the contribution of "internal changes" and "relative-frequency-of-occurrence (RFO) changes" of distinct cloud regime (CR) groups, notable seasonal contrasts of CRE feedback characteristics emerge. Boreal winter CRE feedback is dominated by the positive shortwave CRE (SWCRE) feedback of oceanic low-thick clouds, due to their decreasing RFO as temperature rises. This signal is most likely due to El Niño-Southern Oscillation (ENSO) activity. When ENSO signals are excluded, boreal winter CRE feedback becomes qualitatively similar to the boreal summer feedback, where several CR groups contribute to the total CRE feedback more evenly. Most CR groups' CRE feedbacks largely come from changing RFO (e.g., the predominant transition from oceanic cumulus to broken clouds and more occurrences of higher convective clouds with warming temperature). At the same time, low-thick and broken clouds experience optical thinning and decreasing cloud fraction, and these features are more prominent in boreal summer than winter. Overall, the seasonally asymmetric patterns of CRE feedback, primarily due to ENSO, introduce complexity in assessments of CRE feedback. [ABSTRACT FROM AUTHOR]

Severe convective storms (SCS) and their associated hazards present significant societal risk. Understanding of how these hazards, such as hailfall, may change due to anthropogenic climate change is in its infancy. Previous methods used to investigate possible changes in SCS and their hail used climate model output and were limited by their coarse spatiotemporal resolution and less detailed representations of hail. This study instead uses an event-level pseudo-global warming (PGW) approach to simulate seven different hailstorms in their historical environments, and again in five different end-of-century PGW environments obtained from the worst-case scenario increases in CO2 of five different CMIP5 members. Changes in large-scale environmental parameters were generally found to be consistent with prior studies, showing mostly increases in CAPE, CIN, and precipitable water, with minor changes in vertical wind shear. Nearly all simulated events had moderately stronger updrafts in the PGW environments. Only cold-season events showed an increase in hail sizes both within the storms and at the surface, whereas warm-season events exhibited a decrease in hail sizes at the surface and aloft. Changes in the event-total hailfall area at the ground also showed a seasonal trend, with increases in cold-season events and decreases in warm-season events. Melting depths increased for all PGW environments, and these increases likely contributed to greater rainfall area for warm-season events, where an increase in smaller hail aloft would be more prone to melting. The differences in PGW simulation hail sizes in cold-season and warm-season events found here are likely related to differences in microphysical processes and warrant future study. [ABSTRACT FROM AUTHOR]

The seasonal cycle in temperature is a large and well-observed response to radiative forcing, suggesting its potential as a natural analog to human-caused climate change. Although there have been advances constraining some climate feedback parameters using seasonal observations, the seasonal cycle has not been used to inform about the local temperature sensitivity to greenhouse gas forcing. In this study, we uncover a nonlinear relationship between the amplitude and phase of the seasonal cycle and forced temperature trends in seven CMIP5-era large ensembles across the Northern Hemisphere extratropical continents. We develop a mixture energy balance model that reproduces this relationship and reveals the unexpected finding that the phasing of the seasonal cycle-in addition to the amplitude-contains information about local temperature sensitivity to seasonal forcing over land. Using this energy balance model framework, we compare the pattern and magnitude of the seasonally inferred sensitivity of the surface temperature response to anthropogenic radiative forcing. The seasonally constrained model largely reproduces the pattern of human-caused temperature trends seen in climate models (r = 0.81, p value < 0.01), including polar amplification, but the magnitude of the response is smaller by about a factor of 3. Our results show the relevance of both phasing and amplitude for constraining patterns of local feedbacks and suggest the utility of additional research to better understand the differences in sensitivity between seasonal and greenhouse gas forcing. [ABSTRACT FROM AUTHOR]

Climate projections obtained by running global climate models (GCMs) are subject to multisource uncertainties. The existing framework based on analysis of variance (ANOVA) for decomposing such uncertainties is unable to include the interaction effect between GCM and internal climate variability, which ranks only second to the main effect of GCM in significance. In this study, a three-way ANOVA framework is presented, and all main effects and interaction effects are investigated. The results show that, although the overall uncertainty (O) is mainly contributed by main effects, interaction effects are considerable. Specifically, in the twenty-first century, the global mean (calculated at the grid-cell level and then averaged, and likewise below) relative contributions of all main effects are 54% for precipitation and 82% for temperature; those of all interaction effects are, respectively, 46% and 18%. As the three-way ANOVA cannot investigate the uncertainty components resulting from uncertainty sources, it is improved by deducing the relationship between uncertainty components resulting from uncertainty sources and those resulting from the main effects and interaction effects. By the improved three-way ANOVA, O is decomposed into uncertainty components resulting from the emission scenario (S), GCM(M), and internal climate variability (V). The results reveal that O is mainly contributed by M in the twenty-first century for precipitation, and byMbefore the 2060s whereas by S thereafter for temperature. The robustness of the V characterization is explored by investigating the variation of V on the number of included ensemble members. The extent of the underestimation of the V contribution is roughly an average of 4%for precipitation and 1%for temperature. KEYWORDS: Climate change; Climate prediction; Uncertainty; Climate models; Internal variabilityClimate projections obtained by running global climate models (GCMs) are subject to multisource uncertainties. The existing framework based on analysis of variance (ANOVA) for decomposing such uncertainties is unable to include the interaction effect between GCM and internal climate variability, which ranks only second to the main effect of GCM in significance. In this study, a three-way ANOVA framework is presented, and all main effects and interaction effects are investigated. The results show that, although the overall uncertainty (O) is mainly contributed by main effects, interaction effects are considerable. Specifically, in the twenty-first century, the global mean (calculated at the grid-cell level and then averaged, and likewise below) relative contributions of all main effects are 54% for precipitation and 82% for temperature; those of all interaction effects are, respectively, 46% and 18%. As the three-way ANOVA cannot investigate the uncertainty components resulting from uncertainty sources, it is improved by deducing the relationship between uncertainty components resulting from uncertainty sources and those resulting from the main effects and interaction effects. By the improved three-way ANOVA, O is decomposed into uncertainty components resulting from the emission scenario (S), GCM(M), and internal climate variability (V). The results reveal that O is mainly contributed by M in the twenty-first century for precipitation, and byMbefore the 2060s whereas by S thereafter for temperature. The robustness of the V characterization is explored by investigating the variation of V on the number of included ensemble members. The extent of the underestimation of the V contribution is roughly an average of 4%for precipitation and 1%for temperature. [ABSTRACT FROM AUTHOR]

Solar radiation management (SRM) with injections of aerosols into the stratosphere has emerged as a research area of focus with the potential to cool the planet. However, the amount of SRM required to achieve a given level of cooling, and how this relationship evolves in response to increasing greenhouse gas emissions, remains uncertain. Here, we explore the evolution of solar dimming efficacy over time by defining and quantifying a new SRM feedback term, which is analogous to conventional radiative feedbacks. Using Earth system model simulations that dynamically adjust the amount of insolation to offset global mean warming from increasing CO2, we find that positive SRM feedbacks decrease global planetary albedo and diminish the efficacy of solar dimming. Physically, the decrease in albedo is primarily due to reductions in optically thick tropical cloud fraction in the boundary layer and midtroposphere, which is driven by a drying and destabilization of the tropical mid- to lower troposphere. These results offer an energetic explanation for reduced cloud fraction commonly observed in idealized SRM experiments, as well as reaffirm the need to understand the troposphere response, particularly from clouds, in realizable geoengineering experiments and their potential to feed back onto SRM efficacy. Significance Statement: The goal of this study is to understand how the effectiveness of solar geoengineering may evolve over time. Using a climate model with the ability to directly tune the amount of incoming sunlight, we explore the potential for feedback loops in the climate system to diminish or amplify the desired effect of solar tuning, which is to offset greenhouse gas–induced warming. For this climate model and this solar geoengineering proxy, in particular, we find that feedback loops reduce Earth's albedo and therefore diminish the desired effect of turning down the sun over time. This study lays the groundwork for understanding potential feedback loops in climate model simulations that represent solar geoengineering in a more realistic way. [ABSTRACT FROM AUTHOR]

Projections of precipitation extremes over land are crucial for socioeconomic risk assessments, yet model discrepancies limit their application. Here we use a pattern-filtering technique to identify low-frequency changes in individual members of a multimodel ensemble to assess discrepancies across models in the projected pattern and magnitude of change. Specifically, we apply low-frequency component analysis (LFCA) to the intensity and frequency of daily precipitation extremes over land in 21 CMIP-6 models. LFCA brings modest but statistically significant improvements in the agreement between models in the spatial pattern of projected change, particularly in scenarios with weak greenhouse forcing. Moreover, we show that LFCA facilitates a robust identification of the rates at which increasing precipitation extremes scale with global temperature change within individual ensemble members. While these rates approximately match expectations from the Clausius-Clapeyron relation on average across models, individual models exhibit considerable and significant differences. Monte Carlo simulations indicate that these differences contribute to uncertainty in the magnitude of projected change at least as much as differences in the climate sensitivity. Last, we compare these scaling rates with those identified from observational products, demonstrating that virtually all climate models significantly underestimate the rates at which increases in precipitation extremes have scaled with global temperatures historically. Constraining projections with observations therefore amplifies the projected intensification of precipitation extremes as well as reducing the relative error of their distribution. [ABSTRACT FROM AUTHOR]

Observations and model simulations have confirmed that the higher percentiles of precipitation intensity of all wet days have increased with the local daily dewpoint temperature at the Clausius–Clapeyron (C-C) rate of 7% °C−1 using the binning technique over China. It is uncertain whether the binning scaling rates will remain constant in the future climate. Here, we use daily precipitation and dewpoint temperature (DPT) over China from 20 CMIP6 models to examine and project the change of binning scaling of precipitation extremes. The results of the study suggest that the multimodel ensemble median (MEM) generally captures the spatial distribution of binning scaling rates and binning curves in different climate zones across China. The binning scaling rates have stability in the future but with a large increasing trend (more than 30%) in southeast China in the far future (2061–2100) under the SSP5-8.5 scenario. CMIP6 models project that both the peak of extreme precipitation and the temperature for the plateau mountain zone will increase in the far future under the SSP5-8.5 scenario, implying that the peak structure does not provide an upper limit for future precipitation extremes. Significance Statement: The binning scaling rates describe the relationship between precipitation extremes and temperature based on their day-to-day variations. However, it is still unclear whether the binning scaling rates of daily precipitation extremes with daily temperature will change in the future. We use 20 CMIP6 models to project the scaling rates of precipitation extremes with dewpoint temperature over China in the future. The results show that the sensitivity of precipitation extremes to dewpoint temperature will generally be stable, except that southeast China shows an increasing trend of up to 30%. Moreover, the peak of extreme precipitation and the temperature will increase with warming in the plateau mountain zone. Our results have implications for precipitation prediction and risk assessment. [ABSTRACT FROM AUTHOR]