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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]

The storage of anthropogenic heat in oceans is geographically inhomogeneous, leading to differential warming rates among major ocean basins with notable regional climate impacts. Our analyses of observation-based datasets show that the average warming rate of 0–2000-m Atlantic Ocean since 1960 is nearly threefold stronger than that of the Indo-Pacific Oceans. This feature is robustly captured by historical simulations of phase 6 of Coupled Model Intercomparison Project (CMIP6) and is projected to persist into the future. In CMIP6 simulations, the ocean heat uptake through surface heat fluxes plays a central role in shaping the interbasin warming contrasts. In addition to the slowdown of the Atlantic meridional overturning circulation as stressed in some existing studies, alterations of atmospheric conditions under greenhouse warming are also essential for the increased surface heat flux into the North Atlantic. Specifically, the reduced anthropogenic aerosol concentration in the North Atlantic since the 1980s has been favorable for the enhanced Atlantic Ocean heat uptake in CMIP6 models. Another previously overlooked factor is the geographic shape of the Atlantic Ocean which is relatively wide in midlatitudes and narrow in low latitudes, in contrast to that of the Indo-Pacific Oceans. Combined with the poleward migration of atmospheric circulations, which leads to the meridional pattern of surface heat uptake with broadly enhanced heat uptake in midlatitude oceans due to reduced surface wind speed and cloud cover, the geographic shape effect renders a higher basin-average heat uptake in the Atlantic. [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]

This study estimates extreme rainfall trends across the Gulf Coast and southeastern coast of the United States while applying methods for extending the temporal record and aggregating across spatial trend variations. Nonstationary generalized extreme value (GEV) models are applied to historical annual daily maximum precipitation data (1890–2019) while using CMIP5 global mean surface temperature (GMST) as the covariate. County composites and multicounty regions are used for local data record extension and pooling. Unlike most previous studies, return periods as long as 100 years are analyzed. The local trend estimates themselves are found to be too noisy to be reliable as estimates of climate-driven trends. However, application of a Gaussian process model to the spatial distribution of observed trends yields overall trend detection at the 95% significance level. The overall historical increase due to nonstationarity across the study region, with associated 95% confidence intervals, is 9% (3%, 15%) for the 2-yr return period and 16% (4%, 26%) for the 100-yr return period. A trend is also detectable in the Gulf Coast subregion, but not in the smaller southeast subregion. Recent weather events and nonstationarity have caused the official return value estimates for parts of North and South Carolina to be much lower than the return values estimated here. Significance Statement: Protection of people and infrastructure from flooding relies on accurate estimates of potential extreme rainfall intensity. Some official estimates of extreme rainfall near the Gulf Coast and southeastern coast of the United States are over 20 years old. We show that, across this region, there is a clear trend in daily rainfall so extreme that it only has a 1% chance of happening in any given year (the so-called 100-yr rainfall). This trend means that many existing estimates of extreme rainfall are too low, both now and in the future, so flooding risks based on those estimates would be underestimated as well. [ABSTRACT FROM AUTHOR]

While a poleward shift of the near-surface jet and storm track in response to increased greenhouse gases appears to be robust, the magnitude of this change is uncertain and differs across models, and the mechanisms for this change are poorly constrained. An intermediate complexity GCM is used in this study to explore the factors governing the magnitude of the poleward shift and the mechanisms involved. The degree to which parameterized subgrid-scale convection is inhibited has a leading-order effect on the poleward shift, with a simulation with more convection (and less large-scale precipitation) simulating a significantly weaker shift, and eventually no shift at all if convection is strongly preferred over large-scale precipitation. Many of the physical processes proposed to drive the poleward shift are equally active in all simulations (even those with no poleward shift). Hence, we can conclude that these mechanisms are not of leading-order significance for the poleward shift in any of the simulations. The thermodynamic budget, however, provides useful insight into differences in the jet and storm track response among the simulations. It helps identify midlatitude moisture and latent heat release as a crucial differentiator. These results have implications for intermodel spread in the jet, hydrological cycle, and storm track response to increased greenhouse gases in intermodel comparison projects. [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]

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]

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-use land-cover change (LULCC) plays an important role in weather and climate systems. Human modifications of land cover include building reservoirs and thus creating artificial lakes for multipurpose use. In this research, the authors have completed a Weather Research and Forecasting (WRF) Model-based assessment of impacts of two large parallel lakes on precipitation. This area is located in the western part of the states of Kentucky and Tennessee and known as the Land between the Lakes (LBL). To determine the impacts, this study has replaced the lakes with grass, deciduous forests, and bare soil and conducted model simulations for three precipitation events of different magnitudes. The analysis suggests that precipitation increased in some cases and reduced in others. One of the key impacts of LULCC in the LBL area is the relocation of precipitation cells and also the timing of precipitation. Local precipitation amounts increased or decreased with these relocations. In summary, establishment of lakes or replacement of lakes with alternate land cover may modify local precipitation in the LBL area. [ABSTRACT FROM AUTHOR]

'Neighborhood approaches' have been used in two primary ways to postprocess and verify high-resolution ensemble output. While the two methods appear deceptively similar, they define events over different spatial scales and yield fields with different interpretations: the first produces probabilities interpreted as likelihood of event occurrence at the grid scale, while the second produces probabilities of event occurrence over spatial scales larger than the grid scale. Unfortunately, some studies have confused the two methods, while others did not acknowledge multiple possibilities of neighborhood approach application and simply stated, 'a neighborhood approach was applied' without supporting details. Thus, this paper reviews applications of neighborhood approaches to convection-allowing ensembles in hopes of clarifying the two methods and their different event definitions. Then, using real data, it is demonstrated how the two approaches can yield statistically significantly different objective conclusions about model performance, underscoring the critical need for thorough descriptions of how neighborhood approaches are implemented and events are defined. The authors conclude by providing some recommendations for application of neighborhood approaches to convection-allowing ensembles. [ABSTRACT FROM AUTHOR]

Arctic climate change in winter is tightly linked to changes in the strength of surface temperature inversions, which occur frequently in the present climate as Arctic air masses form during polar night. Recent work proposed that, in a warmer climate, increasing low-cloud optical thickness of maritime air advected over high-latitude landmasses during polar night could suppress the formation of Arctic air masses, amplifying winter warming over continents and sea ice. But this mechanism was based on single-column simulations that could not assess the role of fractional cloud cover change. This paper presents two-dimensional cloud-resolving model simulations that support the single-column model results: low-cloud optical thickness and duration increase strongly with initial air temperature, slowing the surface cooling rate as the climate is warmed. The cloud-resolving model cools less at the surface than the single-column model, and the sensitivity of its cooling to warmer initial temperatures is also higher, because it produces cloudier atmospheres with stronger lower-tropospheric mixing and distributes cloud-top cooling over a deeper atmospheric layer with larger heat capacity. Resolving larger-scale cloud turbulence has the greatest impact on the microphysics schemes that best represent general observed features of mixed-phase clouds, increasing their sensitivity to climate warming. These findings support the hypothesis that increasing insulation of the high-latitude land surface by low clouds in a warmer world could act as a strong positive feedback in future climate change and suggest studying Arctic air formation in a three-dimensional climate model. [ABSTRACT FROM AUTHOR]

This paper improves an extreme-value-theory-based detection and attribution method and then applies it to four types of extreme temperatures, annual minimum daily minimum (TNn) and maximum (TXn) and annual maximum daily minimum (TNx) and maximum (TXx), using the HadEX2 observation and the CMIP5 multimodel simulation datasets of the period 1951-2010 at 17 subcontinent regions. The methodology is an analog of the fingerprinting method adapted to extremes using the generalized extreme value (GEV) distribution. The signals are estimated as the time-dependent location parameters of GEV distributions fitted to extremes simulated by multimodel ensembles under anthropogenic (ANT), natural (NAT), or combined anthropogenic and natural (ALL) external forcings. The observed extremes are modeled by GEV distributions whose location parameters incorporate the signals as covariates. A coordinate descent algorithm improves both computational efficiency and accuracy in comparison to the existing method, facilitating detection of multiple signals simultaneously. An overall goodness-of-fit test was performed at the regional level. The ANT signal was separated from the NAT signal in four to six regions. In these analyses, the waiting times of the 1951-55 20-yr return level in the 2006-10 climate for the temperature of the coldest night and day were found to have increased to over 20 yr; the corresponding waiting times for the warmest night and day were found to have dropped below 20 yr in a majority of the regions. [ABSTRACT FROM AUTHOR]

The role of stationary planetary waves in the dynamical response of the Arctic winter stratosphere circulation to global warming is investigated here by analyzing simulations performed with atmosphere-only models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) driven by prescribed sea surface temperatures (SSTs). Climate models often simulate dynamical warming of the Arctic stratosphere as a response to global warming in association with a strengthening of the deep branch of the Brewer-Dobson circulation; however, until now, no satisfactory mechanism for such a response has been suggested. This study focuses on December-February (DJF) because this is the period when the troposphere and stratosphere are strongly coupled. When forced by increased SSTs, all the models analyzed here simulate Arctic stratosphere dynamical warming, mostly due to increased upward propagation of quasi-stationary wavenumber 1, as diagnosed by the meridional eddy heat flux. Further, it is shown that the stratospheric warming and increased wave flux to the stratosphere are related to the strengthening of the zonal winds in subtropics and midlatitudes near the tropopause. Evidence presented in this paper corroborate climate model simulations of future stratospheric changes and suggest a dynamical warming of the Arctic polar vortex as the most likely response to global warming. [ABSTRACT FROM AUTHOR]

Kretzschmar et al., in a comment in 2017, use the spread in the output of aerosol-climate models to argue that the models refute the hypothesis (presented in a paper by Stevens in 2015) that for the mid-twentieth-century warming to be consistent with observations, then the present-day aerosol forcing, must be less negative than −1 W m−2. The main point of contention is the nature of the relationship between global SO2 emissions and In contrast to the concave (log-linear) relationship used by Stevens and in earlier studies, whereby becomes progressively less sensitive to SO2 emissions, some models suggest a convex relationship, which would imply a less negative lower bound. The model that best exemplifies this difference, and that is most clearly in conflict with the hypothesis of Stevens, does so because of an implausible aerosol response to the initial rise in anthropogenic aerosol precursor emissions in East and South Asia-already in 1975 this model's clear-sky reflectance from anthropogenic aerosol over the North Pacific exceeds present-day estimates of the clear-sky reflectance by the total aerosol. The authors perform experiments using a new (observationally constrained) climatology of anthropogenic aerosols to further show that the effects of changing patterns of aerosol and aerosol precursor emissions during the late twentieth century have, for the same global emissions, relatively little effect on These findings suggest that the behavior Kretzschmar et al. identify as being in conflict with the lower bound in Stevens arises from an implausible relationship between SO2 emissions and and thus provides little basis for revising this lower bound. [ABSTRACT FROM AUTHOR]

This paper describes changes in the climatology, structure, and seasonality of cool-season atmospheric rivers influencing the U.S. West Coast by examining the climate simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) that are forced by the representative concentration pathway (RCP) 8.5 scenario. There are only slight changes in atmospheric river (AR) frequency and seasonality between historical (1970-99) and future (2070-99) periods considering the most extreme days (99th percentile) in integrated water vapor transport (IVT) along the U.S. West Coast. Changes in the 99th percentile of precipitation are only significant over the southern portion of the coast. In contrast, using the number of future days exceeding the historical 99th percentile IVT threshold produces statistically significant increases in the frequency of extreme IVT events for all winter months. The peak in future AR days appears to occur approximately one month earlier. The 10-model mean historical and end-of-century composites of extreme IVT days reflect canonical AR conditions, with a plume of high IVT extending from the coast to the southwest. The similar structure and evolution associated with ARs in the historical and future periods suggest little change in large-scale structure of such events during the upcoming century. Increases in extreme IVT intensity are primarily associated with integrated water vapor increases accompanying a warming climate. Along the southern portion of the U.S. West Coast there is less model agreement regarding the structure and intensity of ARs than along the northern portions of the coast. [ABSTRACT FROM AUTHOR]

Global climate model simulations project that the tropical Andes Mountains of South America, which are particularly vulnerable to climate change because of a reliance on snow and glacial melt for freshwater resources, will experience enhanced warming in the near future, with both higher rates of warming at higher elevations within the mountain range itself and localized enhancement of warming exceeding surrounding areas of the globe. Yet recent surface temperature changes in the tropical Andes do not show evidence for either elevation-dependent warming or regional enhancement of warming on average. However, it remains a possibility that the expected warming trends in this region have begun to manifest in other ways (e.g., in the free atmosphere or at intermediate mountain elevations). This paper proposes evidence from several reanalysis products that there has indeed been a regional enhancement of midtropospheric warming around the central Andes over the past few decades that makes this region stand out as a hot spot within the broader pantropics. This trend is generally not reproduced by historical AMIP climate model simulations, which suggests that the mechanisms through which the atmosphere is warming over the central Andes are not adequately captured by climate models. Possible explanations for localized enhancement of warming in this region are considered. On the other hand, reanalysis products do not consistently exhibit enhanced warming at intermediate mountain elevations in the central Andes as evidenced by the generally moderate rates of change in the freezing-level height, except perhaps in the highest-resolution reanalysis product. [ABSTRACT FROM AUTHOR]

This paper investigates changes in the tropical tropopause layer (TTL) in response to carbon dioxide increase and surface warming separately in an atmospheric general circulation model, finding that both effects lead to a warmer tropical tropopause. Surface warming also results in an upward shift of the tropopause. A detailed heat budget analysis is performed to quantify the contributions from different radiative and dynamic processes to changes in the TTL temperature. When carbon dioxide increases with fixed surface temperature, a warmer TTL mainly results from the direct radiative effect of carbon dioxide increase. With surface warming, the largest contribution to the TTL warming comes from the radiative effect of the warmer troposphere, which is partly canceled by the radiative effect of the moistening at the TTL. Strengthening of the stratospheric circulation following surface warming cools the lower stratosphere dynamically and radiatively via changes in ozone. These two effects are of comparable magnitudes. This circulation change is the main cause of temperature changes near 63 hPa but is weak near 100 hPa. Contributions from changes in convection and clouds are also quantified. These results illustrate the heat budget analysis as a useful tool to disentangle the radiative-dynamical-chemical-convective coupling at the TTL and to facilitate an understanding of intermodel difference. [ABSTRACT FROM AUTHOR]

This paper develops a method for homogenizing daily temperature series. While daily temperatures are statistically more complex than annual or monthly temperatures, techniques and computational methods have been accumulating that can now model and analyze all salient statistical characteristics of daily temperature series. The goal here is to combine these techniques in an efficient manner for multiple changepoint identification in daily series; computational speed is critical as a century of daily data has over 36 500 data points. The method developed here takes into account 1) metadata, 2) reference series, 3) seasonal cycles, and 4) autocorrelation. Autocorrelation is especially important: ignoring it can degrade changepoint techniques, and sample autocorrelations of day-to-day temperature anomalies are often as large as 0.7. While daily homogenization is not conducted as commonly as monthly or annual homogenization, daily analyses provide greater detection precision as they are roughly 30 times as long as monthly records. For example, it is relatively easy to detect two changepoints less than two years apart with daily data, but virtually impossible to flag these in corresponding annually averaged data. The developed methods are shown to work in simulation studies and applied in the analysis of 46 years of daily temperatures from South Haven, Michigan. [ABSTRACT FROM AUTHOR]

Studies have suggested that the persistence in the meridional vacillation of the midlatitude jet (i.e., annular mode time scale) in comprehensive climate models is related to the model biases in climatological jet latitude, with important implications for projections of future climates and midlatitude weather events. Through the use of the recently developed finite-amplitude wave activity formalism and feedback quantifying techniques, this paper has quantified the role of barotropic and baroclinic eddy feedbacks in annular mode time scales using an idealized dry atmospheric model. The eddy-mean flow interaction that characterizes the persistent anomalous state of the midlatitude jet depends on processes associated with the lower-tropospheric source of vertically propagating Rossby waves, baroclinic mechanisms, and processes associated with upper-tropospheric wave propagation and breaking, barotropic mechanisms. A variety of climate change-like thermal forcings are used to generate a range of meridional shifts in the midlatitude eddy-driven jet. The idealized model shows a reduction in annular mode time scale associated with an increase in jet latitude, similar to comprehensive climate models. This decrease in time scale can be attributed to a similar decrease in the strength of the barotropic eddy feedback, which, in the positive phase of the annular mode, is characterized by anomalous potential vorticity (PV) mixing on the equatorward flank of the climatological jet. The decrease in subtropical PV mixing is, in turn, associated with a stronger subtropical jet as the eddy-driven jet is more distant from the subtropics. These results highlight the importance of subtropical eddy-mean flow interactions for the persistence of an eddy-driven jet. [ABSTRACT FROM AUTHOR]

Lakes have been suggested as an indicator of climate change; however, long-term, systematic records of lake temperature are limited. Satellite remote sensing is capable of supporting lake temperature mapping with the advantage of large-area and systematic observations. The goal of this research application was to assess spatiotemporal trends in lake skin temperature for all lakes over 8 ha across northern New England for the past three decades. Nearly 10 000 Landsat scenes for July, August, and September from 1984 to 2014 were processed using MODTRAN and MERRA parameterizations to generate atmospherically corrected lake skin temperature records. Results show, on average, lakes warmed at a rate of 0.8°C decade-1, with smaller lakes warming at a faster rate. Complementing regression and space--time analyses showed similar results (R² = 0.63) for lake temperature trends and found lakes, on average, are warming faster than daily maximumorminimum air temperature. Nomajor hot spots were found as lake temperature changes were heterogeneous on a local scale and evenly distributed across the region. Maximum and minimum daily temperature, lake size, and elevation were found as significant drivers of lake temperature. This effort provides the first regionally focused and comprehensive spatiotemporal assessment of thousands (n = 3955) of lakes concentrated in one geographic region. The approach is scalable and adaptable to any region for assessing lake temperature trends and potential drivers. [ABSTRACT FROM AUTHOR]

In fields such as climate science, it is common to compile an ensemble of different simulators for the same underlying process. It is a striking observation that the ensemble mean often outperforms at least half of the ensemble members in mean squared error (measured with respect to observations). In fact, as demonstrated in the most recent IPCC report, the ensemble mean often outperforms all or almost all of the ensemble members across a range of climate variables. This paper shows that these could be mathematical results based on convexity and averaging but with implications for the properties of the current generation of climate simulators. [ABSTRACT FROM AUTHOR]

This fifth edition of explaining extreme events of the previous year (2015) from a climate perspective continues to provide evidence that climate change is altering some extreme event risk. Without exception, all the heat-related events studied in this year's report were found to have been made more intense or likely due to human-induced climate change, and this was discernible even for those events strongly influenced by the 2015 El Niño. Furthermore, many papers in this year's report demonstrate that attribution science is capable of separating the effects of natural drivers including the strong 2015 El Niño from the influences of long-term human-induced climate change. Other event types investigated include cold winters, tropical cyclone activity, extreme sunshine in the United Kingdom, tidal flooding, precipitation, drought, reduced snowpack in the U.S. mountain west, arctic sea ice extent, and wildfires in Alaska. Two studies investigated extreme cold waves and monthly-mean cold conditions over eastern North America during 2015, and find these not to have been symptomatic of human-induced climate change. Instead, they find the cold conditions were caused primarily by internally generated natural variability. One of these studies shows winters are becoming warmer, less variable, with no increase in daily temperature extremes over the eastern United States. Tropical cyclone activity was extreme in 2015 in the western North Pacific (WNP) as measured by accumulated cyclone energy (ACE). In this report, a study finds that human-caused climate change largely increased the odds of this extreme cyclone activity season. The 2015 Alaska fire season burned the second largest number of acres since records began in 1940. Investigators find that human-induced climate change has increased the likelihood of a fire season of this severity. Confidence in results and ability to quickly do an attribution analysis depend on the "three pillars" of event attribution: the quality of the observational record, the ability of models to simulate the event, and our understanding of the physical processes that drive the event and how they are being impacted by climate change. A result that does not find a role for climate change may be because one or more of these three elements is insufficient to draw a clear conclusion. As these pillars are strengthened for different event types, confidence in the presence and absence of a climate change influence will increase. This year researchers also link how changes in extreme event risk impact human health and discomfort during heat waves, specifically by looking at the role of climate change on the wet bulb globe temperature during a deadly heat wave in Egypt. This report reflects a growing interest within the attribution community to connect attribution science to societal impacts to inform risk management through "impact attribution." Many will watch with great interest as this area of research evolves in the coming years. INSET: EDITORIAL AND PRODUCTION TEAM. [ABSTRACT FROM AUTHOR]

The 35-yr NOAA Advanced Very High Resolution Radiometer (AVHRR) observation record offers an excellent opportunity to study decadal climate variability, provided that all participating AVHRR instruments are calibrated on a consistent radiometric scale. Because of the lack of onboard calibration systems, the solar imaging channels of the AVHRR must be vicariously calibrated using invariant Earth targets as a calibrated reference source. The greatest challenge in calibrating the AVHRR dataset is the orbit degradation of the NOAA satellites, which eventually drift into a terminator orbit several years after launch. Therefore, the invariant targets must be characterized over the full range of solar zenith angles (SZAs) sampled by the satellite instrument. This study outlines a multiple invariant Earth target calibration approach specifically designed to account for the degrading NOAA orbits. The desert, polar ice, and deep convective cloud (DCC) invariant targets are characterized over all observed SZAs using NOAA-16 AVHRR measurements, which are referenced to the Aqua MODIS Collection 6 calibration via direct transfer of the MODIS calibration to the NOAA-16 AVHRR instrument using simultaneous nadir overpass (SNO) observations over the North Pole. The multiple invariant target calibrations are combined using the inverse of their temporal variance to optimize the resulting calibration stability. The NOAA-18 AVHRR gains derived using the desert, polar ice, and DCC targets, as well as from SNO, were found consistent within 1%, thereby validating that the Aqua MODIS calibration is effectively transferred to the reference calibration targets. The companion paper, Part II, applies the methodology across the AVHRR record to derive the sensor-specific calibration coefficients. [ABSTRACT FROM AUTHOR]

Intensification of extreme rainfall due to climate change means that federally published rainfall metrics such as the "100-yr storm" are outdated throughout much of the United States. Given their central role in a wide range of infrastructure designs and risk management decisions, updating these metrics to reflect recent and future changes is essential to protect communities. There have been considerable advances in recent years in data collection, statistical methods, and climate modeling that can now be brought to bear on the problem. Scientists must take a lead in this updating process, which should be open, inclusive, and leverage recent scientific advances. [ABSTRACT FROM AUTHOR]

The vertical velocity distribution in the atmosphere is asymmetric with stronger upward than downward motion. This asymmetry is important for the distribution of precipitation and its extremes and for an effective static stability that has been used to represent the effects of latent heating on extratropical eddies. Idealized GCM simulations show that the asymmetry increases as the climate warms, but current moist dynamical theories based around small-amplitude modes greatly overestimate the increase in asymmetry with warming found in the simulations. Here, we first analyze the changes in asymmetry with warming using numerical inversions of a moist quasigeostrophic omega equation applied to output from the idealized GCM. The inversions show that increases in the asymmetry with warming in the GCM simulations are primarily related to decreases in moist static stability on the left-hand side of the moist omega equation, whereas the dynamical forcing on the right-hand side of the omega equation is unskewed and contributes little to the asymmetry of the vertical velocity distribution. By contrast, increases in asymmetry with warming for small-amplitude modes are related to changes in both moist static stability and dynamical forcing leading to enhanced asymmetry in warm climates. We distill these insights into a toy model of the moist omega equation that is solved for a given moist static stability and wavenumber of the dynamical forcing. In comparison to modal theory, the toy model better reproduces the slow increase of the asymmetry with climate warming in the idealized GCM simulations and over the seasonal cycle from winter to summer in reanalysis. Significance Statement: Upward velocities are stronger than downward velocities in the atmosphere, and this asymmetry is important for the distribution of precipitation because precipitation is linked to upward motion. An important and open question is what sets this asymmetry and how much it increases as the climate warms. Past work has shown that current theories greatly overestimate the increase in asymmetry with warming in idealized simulations. In this work, we develop a more complete theory and show that it is able to better reproduce the slow increase of the asymmetry with warming that is found over the seasonal cycle from winter to summer and in idealized simulations of warming climates. [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 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]

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]

Large temperature variations in a temperate climate, particularly in late winter and early spring, can be disruptive for native ecosystems and agricultural crops. As warmer temperatures occur earlier in the year in midlatitude regions as a result of anthropogenic climate change, springtime temperatures may become less consistent, leading to potential damage to species and crops that are vulnerable to the return of historically cooler temperatures, including late-spring frosts, after an initial warm-up. In this work, we quantify shifting patterns in late-winter and springtime temperature variations at eight sites across New Jersey from 1950 to 2019. Many sites located along the coast or in the coastal plain experience increases in the number of times the temperature climbs above 15.5°C (60°F) and then falls below freezing (i.e.,0°C, or 32°F). Sites in southern New Jersey (where much of the state's agriculture is located) experience the most significant (P < 0.05) increases in large springtime temperature variations. Across all sites, there is a general increase in both the percentage and magnitude of temperature variations that occur as early as February. At 75% of sites, day-to-day variation in daily maximum temperature has increased from the 1950s through 2019; day-to-day variation in daily minimum temperatures has increased over the same time at more than half of sites considered. These amplifications in extreme temperature variations indicate the need for both mitigation and adaptation strategies to protect vulnerable crops and ecosystems in the region during this critical time of the year. Significance Statement: Human-caused climate change has made it more likely for warmer temperatures to occur earlier in the year, causing many locations to experience late-winter and early-springtime temperatures that are less consistent than they may have been in the past. These variations can be highly problematic for both vital agricultural crops and critical ecosystems. Here, we evaluate how late-winter and early-springtime temperatures have changed throughout New Jersey (home to a variety of agriculture and unique ecosystems) from the mid-twentieth century until 2019. We find critical changes to temperature patterns during late winter and early spring, including larger and more frequent temperature swings (particularly in February) and increased day-to-day variation in high and low temperatures. [ABSTRACT FROM AUTHOR]

Climate change has a profound effect on Arctic meteorology extreme events, such as rain-on-snow (ROS), which affects surface state variable spatial and temporal variability. Passive microwave satellite images can help detect such events in polar regions where local meteorological and snow information is scarce. In this study, we use a detection algorithm using high-resolution passive microwave data to monitor spatial and temporal variability of ROS over the Canadian Arctic Archipelago from 1987 to 2019. The method is validated using data from several meteorological stations and atmospheric corrections have been applied to the passive microwave dataset. Our approach to detect ROS is based on two methods: 1) over a fixed time period (i.e., 1 November–31 May) throughout the study period and 2) using an a priori detection for snow presence before applying our ROS algorithm (i.e., length of studied winter varies yearly). Event occurrence is analyzed for each winter and separated by island groups of the Canadian Arctic Archipelago. Results show an increase in absolute ROS occurrence, mainly along the coasts, although no statistically significant trends are observed. Significance Statement: Rain-on-snow (ROS) is known to have significant consequences on vegetation and fauna, especially widespread events. This study aimed to use a recent high-resolution dataset of passive microwave observations to investigate spatial and temporal trends in ROS occurrence in the Arctic. Results show that a global increase in event occurrence can be observed across the arctic. [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]

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]

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]

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 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]

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]

The effect of climate warming in response to rising atmospheric CO2 on the ventilation of the ocean remains uncertain. Here we make theoretical advances in elucidating the relationship between ideal age and transit time distribution (TTD) in a time-dependent flow. Subsequently, we develop an offline tracer-transport model to characterize the ventilation patterns and time scales in the time-evolving circulation for the 1850–2300 period as simulated with the Community Earth System Model version 1 (CESMv1) under a business-as-usual warming scenario. We found that by 2300 2.1% less water originates from the high-latitude deep water formation regions (both hemispheres) compared to 1850. In compensation, there is an increase in the water originating from the subantarctic. We also found that slowing meridional overturning circulation causes a gradual increase in mean age during the 1850–2300 period, with a globally averaged mean-age increase of ∼110 years in 2300. Where and when the water will be re-exposed to the atmosphere depends on the post-2300 circulation. For example, if we assume that the circulation persists in its year-2300 state (scenario 1), the mean interior-to-surface transit time in year 1850 is ∼1140 years. In contrast, if we assume that the circulation abruptly recovers to its year-1850 state (scenario 2), the mean interior-to-surface transit time in 1850 is only ∼740 years. By 2300, these differences become even larger; in scenario 1, the mean interior-to-surface transit time increases by ∼200 years, whereas scenario 2 decreases by ∼80 years. The dependence of interior-to-surface transit time on the future ocean circulation produces an additional unavoidable uncertainty in the long-term durability of marine carbon dioxide removal strategies. Significance Statement: The ocean's circulation, when altered by climate warming, can affect its capacity to absorb heat and CO2, which are crucial for the global climate. In our study, we investigated how global warming, caused by rising CO2 levels, might impact the ocean circulation—the way water moves from deep ocean to the surface and vice versa. We discovered that by 2300, if we continue on our current warming trajectory, the origins of water within the ocean will shift, with less coming from deep, cold zones near the poles and more from subantarctic regions. As a result, deep water will take longer time before it resurfaces than shallow water. How quickly this water travels from deep regions to the surface could change, depending on the state of future ocean circulation. If the circulation remains as predicted in 2300, this journey will take longer. Conversely, if it reverts to the pattern in 1850, the process will be quicker. This variability introduces added uncertainty to strategies aimed at mitigating climate change by storing CO2 in the ocean. Our work highlights the intricate ways in which climate change can influence our oceans, potentially affecting our plans to mitigate global warming. [ABSTRACT FROM AUTHOR]

Because they are rare, extreme weather events have critical impacts on societies and ecosystems and attract public and scientific attention. The most unusual events are regularly documented as part of routine climate monitoring by meteorological services. A growing number of attribution studies also aim at quantifying how their probability has evolved under human-induced climate change. However, it is often recognized that (i) the selection of studied events is geographically uneven, and (ii) the definition of a given event, in particular, its spatiotemporal scale, is subjective, which may impact attribution statements. Here we present an original method that objectively selects, defines, and compares extreme events that have occurred worldwide in the recent years. Building on previous work, the event definition consists of automatically selecting the spatiotemporal scale that maximizes the event rarity, accounting for the nonstationary context of climate change. We then explore all years, seasons, and regions and search for the most extreme events. We demonstrate how our searching procedure can be both useful for climate monitoring over a given territory, and resolve the geographical selection bias of attribution studies. Ultimately, we provide a selection of the most exceptional hot and cold events in the recent past, among which are iconic heatwaves such as those seen in 2021 in Canada and in 2003 in Europe. [ABSTRACT FROM AUTHOR]

As the global research enterprise grapples with the challenge of a low-carbon future, a key challenge is the future of international conferences. An emerging initiative that combines elements of the traditional in-person conference and a virtual conference is a multi-hub approach. Here we report on a real-world trial of a multi-hub approach, the World Climate Research Programme/Stratosphere-Troposphere Processes and their Role in Climate (WCRP/SPARC) General Assembly held in Qingdao-Reading-Boulder during the last week of October 2022 with more than 400 participants. While there are other examples of conferences run in dual-hub or hybrid online and in-person formats, we are not aware of other large atmospheric science conferences held in this format. Based on travel surveys of participants, we estimate that the multi-hub approach reduced the carbon footprint from travel by between a factor of 2.3 and 4.1 times the footprint when hosting the conference in a single location. This resulted in a saving of at least 288 tonnes of carbon dioxide equivalent (tCO2eq) and perhaps as much as 683 tCO2eq, compared to having the conference in one location only. Feedback from participants, collected immediately after the conference, showed that the majority would again attend another conference in a similar format. There are many ways that the format of the SPARC General Assembly could have been improved, but this proof of concept provides an inspiration to other groups to give the multi-hub format a try. [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]