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A thermodynamic energy budget analysis is applied to the lowest model level of the ERA5 dataset to investigate the mechanisms that drive the growth and decay of extreme positive surface air temperature (SAT) events. Regional and seasonal variation of the mechanisms are investigated. For each grid point on Earth's surface, a separate composite analysis is performed for extreme SAT events, which are days when temperature anomaly exceeds the 95th percentile. Among the dynamical terms, horizontal temperature advection of the climatological temperature by the anomalous wind dominates SAT anomaly growth over the extratropics, while nonlinear horizontal temperature advection is a major factor over high-latitude regions and the adiabatic warming is important over major mountainous regions. During the decay period, advection of the climatological temperature by the anomalous wind sustains the warming while nonlinear advection becomes the dominant decay mechanism. Among diabatic heating processes, vertical mixing contributes to the SAT anomaly growth over most locations while longwave radiative cooling hinders SAT anomaly growth, especially over the ocean. However, over arid regions during summer, longwave heating largely contributes to SAT anomaly growth while the vertical mixing dampens the SAT anomaly growth. During the decay period, both longwave cooling and vertical mixing contribute to SAT anomaly decay with more pronounced effects over the ocean and land, respectively. These regional and seasonal characteristics of the processes that drive extreme SAT events can serve as a benchmark for understanding the future behavior of extreme weather. [ABSTRACT FROM AUTHOR]

This study identifies a significantly positive relationship between summer surface air temperature (SAT) anomalies over two remote regions in the Eurasian continent and North America during the period 1979–2021 on the interannual time scale. The former region includes the East European Plain and the West Siberian Plain, and the latter region includes central and eastern North America. The regionally averaged summer SAT anomalies show a correlation coefficient of 0.66 between these two regions, which is significant at the 99% confidence level. This intercontinental SAT relationship can be explained by a wavelike pattern of circulation anomalies, which is the leading mode of upper-tropospheric circulation anomalies over the middle and high latitudes of the Northern Hemisphere in summer. Further analysis suggests that the sea surface temperature (SST) anomalies over the Pacific and North Atlantic in the preceding spring, being coupled with the leading mode of atmospheric circulation anomalies over the Pacific–Atlantic sector, persist into summer and affect the SATs in the two remote regions, resulting in the intercontinental SAT connection. Significance Statement: Summer surface air temperature (SAT) has profound effects on public health and agricultural production. Here we find a significantly positive relationship between interannual variations of summer SATs over two remote regions, one in the Eurasian continent and the other in North America. This intercontinental relationship in SATs can be explained as a result of atmosphere–ocean coupling over the Pacific and North Atlantic in the preceding spring. The result is likely to be a critical implication for the seasonal forecast of SAT variations over the two regions. In addition, the concurrence of higher or lower temperatures in these two regions may have impacts on global grain production, since these two regions include many major grain-producing areas in the world. [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]

Using the observational and reanalysis datasets during the period of 1979–2018, this study examines the modulation effects of the Atlantic multidecadal oscillation (AMO) and Pacific decadal oscillation (PDO) on the interdecadal change in summer surface air temperature (SAT) over the eastern Tibetan Plateau (TP). The results show that the eastern TP has experienced a remarkable warming in boreal summer since 1997. In addition, the warming is associated with simultaneously enhanced westward water vapor transport and the northward shift of the subtropical westerly jet (SWJ) over the northeast of the TP. Further research indicates that both water vapor transport and the SWJ are modulated by the PDO and AMO on interdecadal time scales. Since the late 1990s, the PDO has changed from the positive to negative phase, while the AMO has changed from the negative to positive phase. The change in the out-of-phase combination of the PDO and AMO has resulted in a northward shift of the SWJ at 200 hPa near the northeast of the TP through the Rossby wave train originating from the northwestern Atlantic. In addition, the PDO and AMO could both affect the Rossby wave train. From the northwestern Atlantic to Eurasia, the wave train may be dominated by the PDO, while the wave train near the TP is dominated by the AMO. The anomalous anticyclone over the northeastern TP is part of the Rossby wave train, causing the northward shift of the SWJ, favoring the intrusion of the water vapor from the eastern China into the eastern TP, thus leading to the TP warming. Significance Statement: It is understood that the Tibetan Plateau (TP) may be among the most sensitive regions to the global climate change. In addition, this region has warmed very rapidly in the latter half of the twentieth century. Based on the statistical analysis and dynamic diagnostics, the influences of interdecadal variations of atmospheric circulations on summer surface air temperature (SAT) over the eastern TP were analyzed for the years 1979 to 2018. We found that the eastern TP experienced an increase in summer SAT. In addition, the interdecadal change in SAT over the eastern TP is strongly affected by the water vapor transport and the subtropical westerly jet. Further analyses show that the PDO and AMO were the key factors influencing summer SAT over the eastern TP on the interdecadal time scales. The PDO and AMO could both affect the Rossby wave train. From the northwest Atlantic to Eurasia, the wave train may be dominated by the PDO, while the wave train near the TP is dominated by the AMO. In addition, the northwest Atlantic SSTs, which are dominated by the AMO, could also affect the SAT over the eastern TP by the Rossby wave train. [ABSTRACT FROM AUTHOR]

El Niño is known to affect Arctic temperature. However, the robustness of the observed relationship between El Niño and Arctic temperature remains debated. Here we reexamine the impacts of El Niño on the Arctic temperature in boreal winter [December–February (DJF)] using reanalysis datasets and atmospheric model experiments. This study shows that extreme El Niño events are accompanied by significant boreal winter cooling over northeastern Canada and Greenland (NECG), while moderate eastern Pacific (MEP) El Niño events are accompanied by significant boreal winter warming in this region. For central Pacific (CP) El Niño events, a cold signal appears in NECG, but with no statistical significance. During extreme El Niño winters, a positive Pacific–North America (PNA)-like pattern is seen in the Pacific, and anomalously negative 200-hPa geopotential height (Z200) strengthening occurs over NECG, which is a response to anomalous strong wave activity originating in the tropical Pacific. El Niño–induced circulation anomalies can further induce NECG cooling via cold temperature advection and decreased downward longwave radiation. In contrast, for the MEP El Niño, the subtropical jet extends zonally from the North Pacific to the North Atlantic, which is accompanied by increased baroclinicity anomalies and favors the propagation of synoptic eddies into the Atlantic, leading to a negative North Atlantic Oscillation (NAO)-like pattern. This in turn could further enhance the positive Z200 anomalies over NECG, resulting in anomalous warming in NECG through warm temperature advection and enhanced downward longwave radiation. A series of atmospheric model experiments simulates the observed circulation changes and associated warming over NECG. Significance Statement: This work investigates the different impacts of the three El Niño types on regional Arctic wintertime temperature anomalies based on observations and model experiments. The impacts of El Niño events on northeastern Canada and Greenland temperatures during boreal winter show distinct differences between extreme El Niño and moderate EP El Niño events. These distinct differences can be attributed to the different atmospheric circulation patterns induced by different SST patterns, which can lead to warm (cold) temperature advection and enhanced (decreased) downward longwave radiation. These results highlight the different impacts of extreme and moderate EP El Niños on Arctic temperatures and provide an improved understanding of the impact of El Niños on the Arctic climate. [ABSTRACT FROM AUTHOR]

It has been well known that the preceding winter ENSO affects the atmospheric convection over the tropical western North Pacific (WNP) in summer, which has important impacts on Asian climate. However, more than half of the interannual variance in tropical WNP convection cannot be explained by ENSO. This study separates the WNP convection into two components, namely, independent of and dependent on the preceding winter ENSO, and compares the anomalies associated with these two components. The linear regression results indicate that the independent convection suppression corresponds to significant cyclonic anomalies over East Asia in both the lower and upper troposphere, and correspondingly a southward displacement of upper-tropospheric East Asian westerly jet. By contrast, these circulation anomalies are weakened for the dependent convection suppression, which is more closely related to the lower-tropospheric cyclonic anomalies over the Indian Ocean. Accordingly, the independent and dependent components exert distinct impacts on rainfall and temperature in Asia. Specifically, the independent suppression corresponds to more significantly enhanced rainfall in subtropical East Asia compared with the dependent one. Moreover, there are colder surface air temperatures in the midlatitude East Asia for the independent suppression and warmer temperatures in South and Southeast Asia for the dependent suppression. Further analyses suggest that the circulation and climate anomalies for the independent component are mainly contributed by July and August, while those for the dependent component become weak from June to August. These results can be helpful for a better understanding of summer Asian climate variability and predictability. [ABSTRACT FROM AUTHOR]

A strong coherence of the summer (June–August) surface air temperature (SAT) anomalies exists over eastern Eurasia (EE) and central Eurasia (CE) in association with a remarkable intraseasonal (10–90-day) variability. The intraseasonal SAT over Eurasia shows a negative correlation between EE and CE, which is closely related to an intraseasonal wave train at the upper troposphere over the mid–high latitudes of Eurasia. The wave train propagates eastward and results in the intraseasonal variation of SAT in a seesaw pattern. The column-integrated temperature budget suggests that both the horizontal and vertical advection are important for the intraseasonal SAT dipole. More specifically, the climatological westerly, intraseasonal meridional wind anomaly, and the anomalous vertical motion play dominant roles in perturbing temperature over the CE and EE regions, while the diabatic heating is a negative feedback. The propagation of the Rossby wave train in the upper troposphere helps to maintain the circulation anomalies associated with the SAT seesaw. The leading modes of meridional wind anomalies at 200 hPa over the Eurasian high latitudes resemble the intraseasonal wave train, indicating that the wave train associated with the SAT seesaw is an atmospheric intrinsic mode over the mid–high latitudes. This study also investigates the impact of the intraseasonal SAT seesaw on regional heat wave events. It is suggested that the intraseasonal SAT seesaw has a major influence on the variability of heat wave events over both EE and CE, which may provide great implications for regional subseasonal forecasts of extreme weather events. [ABSTRACT FROM AUTHOR]

This study investigates the influence of the Atlantic multidecadal oscillation (AMO) on the multidecadal variability of winter surface air temperature in arid central Asia (ACASAT). Apart from a long-term warming trend, the observational analysis shows that the winter ACASAT exhibits a significant multidecadal variability, which is characterized by antiphase fluctuations with the AMO. The mechanism for this negative correlation between the AMO and the winter ACASAT is explored from the aspect of wave teleconnection. The AMO provides energy for the Scandinavian teleconnection pattern at middle and low altitudes by regulating the high-altitude wave train over the middle and high latitudes of Eurasia, and thus has an impact on the remote climate in arid central Asia. Results from the linear baroclinic model (LBM) provide evidence for the linkage between the AMO and the Scandinavian teleconnection pattern. When the AMO is in its warm periods, the Scandinavian teleconnection pattern is in a positive phase, which further makes the cold air from the northeast strengthen, leading to the anomalously colder surface air temperature in arid central Asia. Based on the relationship that the North Atlantic Oscillation (NAO) leads the AMO by 15–20 years, it is further found that there is a leading relationship between the NAO and the winter ACASAT via the AMO. On this basis, an empirical model using the NAO as a predictor was established to predict the ACASAT, and the empirical model shows good hindcast performance. Results from the model show that the winter ACASAT will continue to rise in the next 10 years and decline after 2030. [ABSTRACT FROM AUTHOR]

Physically based observational constraint methods can effectively reduce uncertainty in global warming projections but have not been widely applied at regional scales. We first develop and apply multivariate linear regression models for constraining projections of surface air temperature averaged over subcontinental regions in the extratropical Northern Hemisphere, based on a set of potential constraints including climatological metrics derived from tropical and subtropical low-level cloud and global average past warming trend, as well as a set of regional climate metrics previously used in the literature. We evaluate the performance of the multivariate linear regression models based on cross-validated tests using output from phases 5 and 6 of the Coupled Model Intercomparison Projects (CMIP). We find that linear regression models using global-scale low-cloud metrics alone perform more robustly than linear regression models using the past global mean warming trend or regional climate metrics as constraints. These results, while favoring global constraints over the set of regional constraints considered, do not preclude the existence of even better regional constraints for particular regions. Through model-based cross-validation, the projections constrained using low-level cloud metrics exhibit more accurate best estimate projections, narrower uncertainty ranges, and more reliable uncertainty estimates in most Northern Hemisphere regions when compared with unconstrained projections. Application of the approach to climate projections based on both Shared Socioeconomic Pathway (SSP) 1-2.6 and SSP5-8.5 using observed low-cloud metrics results in considerably narrower 5%–95% uncertainty ranges of twenty-first-century warming over subcontinental Northern Hemisphere land regions compared to unconstrained projections. [ABSTRACT FROM AUTHOR]

The predictability of temperatures in North America is of great importance for local agriculture and human health. In autumn (SON), the temperature in North America is correlated with ENSO, but its predictive skill is limited. Here, we show that spring (MAM) sea surface temperature (SST) anomalies in the southwest Pacific (SWP) exhibit a higher correlation with autumn temperature in North America (r = 0.73) than ENSO. This cross-seasonal and cross-hemispheric relationship is established via the western tropical Pacific (WTP) region. The spring SWP SST anomalies show a cross-hemispheric propagation embedded in the southerly monsoonal flow through the wind–evaporation–SST feedback, which sustains the progression of SST anomalies toward the WTP in autumn. The AGCM simulations from multimodels show that active convection in the WTP caused by SST warming stimulate a Rossby wave train propagating downward to North America, where it is governed by an anomalous high with increased atmospheric thickness and tropospheric temperature. Consequently, the longwave radiative heating over North America is enhanced, raising the surface air temperature. These results indicate that the SWP SST is a useful predictor of North American temperature 6 months in advance through the cross-hemispheric influence. A model based on the spring SWP SST and preceding winter ENSO (Niño-3.4) shows a high predictive skill for the autumn temperature anomalies in North America. Significance Statement: Seasonal predictions of surface temperature are important for agricultural decision-making, disaster prevention, and mitigation. Over the western Pacific, associated with the seasonal evolution of ITCZ, there is a strong northward progression of SST anomaly signals generated in the southwest Pacific. This study finds that this cross-hemispheric SST propagation can significantly impact the autumn surface temperature over central North America through the atmospheric bridge. A statistical model incorporating southwest Pacific SST for spring is constructed to predict the North American autumn surface temperature and exhibits high consistency with observations. This improves our understanding of the interhemispheric interactions at seasonal time scales and the seasonal predictability of the North American climate. [ABSTRACT FROM AUTHOR]

Against the backdrop of global warming, the Eurasian continent and its surrounding areas have experienced ununiform warming in recent decades. Variations in the meridional thermal contrast (MTC) in East Asia and its adjacent regions have a critical influence on the East Asian summer monsoon (EASM); therefore, its forcings were analyzed in this study. The results show that the MTC in East Asia and the surrounding regions showed significant decadal changes during the interval 1960–2014, with a decadal strengthening in the late 1970s and a decadal weakening in the late 1990s. Further investigation showed that internal variability was the dominant control on these two decadal changes of MTC, accounting for 135% and 78.5% of the two observed changes in the 1970s and 1990s, respectively. Based on pacemaker experiments and a method that reconstructs decadal changes in the interdecadal Pacific oscillation (IPO), we found that a positive phase of the IPO tends to cause cooling in the low latitudes and warming in the mid–high latitudes and that a negative phase of the IPO tends to cause warming in the low latitudes and cooling in the mid–high latitudes, which in turn can explain 54.4% and 35.8% of the two internally generated decadal changes in the MTC, respectively. The Atlantic multidecadal oscillation (AMO), when in the same phase as the IPO, exhibits an opposing pattern of surface air temperature. This only had a significant influence in the late 1990s, where it explained 37.9% of the internally generated decadal changes in the MTC. Our findings highlight that internal variability, especially that relating to the IPO and the AMO, should be considered when predicting future changes in thermal conditions in East Asia and its adjacent regions. [ABSTRACT FROM AUTHOR]

A new wintertime surface air temperature (SAT) pattern, called the Asia–Kuroshio and Oyashio Extension–North America (AKNA) pattern, is identified over the pan–North Pacific region (85°E–85°W, 25°–65°N) based on NCEP reanalysis data. The AKNA pattern is likely to influence the climate of the extratropical area of Asia and North America via two SAT dipoles and has a significant impact on the wintertime extremely cold weather along the eastern coastal regions of East Asia. Simulations using an atmospheric general circulation model indicate that wintertime sea surface temperature anomalies (SSTa) in the Kuroshio and Oyashio Extension (KOE) region can force an equivalent barotropic atmospheric ridge downstream and weaken the Siberian high and Alaska atmospheric ridge, resulting in the formation of the AKNA pattern. This circulation pattern tends to intensify the midlatitude (40°–60°N) westerlies over East Asia, which inhibits the southward invasion of the cold air into southern East Asia. Further diagnostic analysis indicates that the KOE SSTa can modulate the variation of storm track and westerlies by affecting baroclinic instability and eddy–mean flow interaction. Moreover, the KOE SSTa can provide a favorable environment for the development of the local atmospheric ascending motion and secondary circulation across the KOE SSTa, thereby affecting variability of the free atmosphere. Significance Statement: This study aims to build a connection between the wintertime extratropical climate and the variation of the Kuroshio and Oyashio Extension. This work isolated a new wintertime surface air temperature (SAT) pattern over mid–high-latitude Asia and North America, which explains a considerable proportion of cold extremes over the eastern regions of East Asia. The reanalysis data and model simulations indicate that the temporal variability of the SAT pattern is influenced by the change of sea surface temperature in the Kuroshio and Oyashio Extension. These findings emphasize the important role of midlatitude air–sea interaction in the modulation of the mid–high-latitude climate. [ABSTRACT FROM AUTHOR]

Snow cover (SC) is an important contributor to atmospheric predictability on subseasonal to seasonal time scales. This paper evaluates the submonthly scale cause-and-effect relationship between SC and surface air temperature (SAT) in Eurasia, which has been typically overlooked in previous statistical analyses of subseasonal to seasonal atmospheric predictability. We focus on the November east–west dipolar SC pattern, a dominant large-scale SC phenomenon. We use an information flow analysis, based on information theory, to infer causal relations not revealed by conventional correlation analysis. This analysis indicates a one-way causality from SAT to SC around the west pole (Europe) in boreal autumn (November), implying that SC has little influence on the time evolution of SAT. In contrast, causality from SC to SAT is significant around the east pole (the Mongolian Plateau). An atmospheric model experiment suggests that the SAT response to SC can persist for a month via snow–albedo feedback, although the response of the upper atmosphere in the model is small. Furthermore, the subseasonal hindcasts show that the contribution of SC may affect the predictability of SAT for up to four weeks around the east pole. We suggest that the geographical and climatological atmospheric conditions are favorable for generating a positive albedo feedback as a “hotspot” of SC–SAT coupling around the east pole in autumn. The agreement of our causality analysis with other analytical and modeling approaches underscores the cause-and-effect relationship between SC and SAT and its contribution to the subseasonal predictability over autumnal Eurasia. [ABSTRACT FROM AUTHOR]

It is well known that El Niño–Southern Oscillation (ENSO) can influence the East Asian winter climate by modifying the atmospheric circulation over the western North Pacific (WNP). While the impact on precipitation in southeastern China has been extensively studied, the ENSO signal in surface air temperature (SAT) remains overlooked. In this paper, we identify robust ENSO footprints in the winter daily minimum SAT in southeastern China, with El Niño winters generally accompanied by warmer-than-normal minimum SAT anomalies. In contrast, the responses of maximum SAT are weak and negligible, suggesting a diurnal cycle–dependent ENSO influence. Further analysis indicates that this diurnal cycle dependence stems primarily from the disparate surface radiative heating between day and night induced by ENSO-related local total cloud cover (TCC) change. The warmer minimum SAT occurring in the early morning of El Niño winters is mainly caused by the enhanced surface downward longwave radiative heating as a result of the TCC increase. However, in the afternoon of El Niño winters, although the anomalous horizontal advection of warm air plays a role, there is surface radiative cooling as the weakening of solar radiation due to TCC reflection overwhelms the increase in downward longwave radiation, which leads to a weakened sensible heat flux and thus has a cooling effect on the SAT. Ultimately, these two processes effectively cancel each other out and together produce insignificant maximum SAT responses. Our conclusions carry important implications for the seasonal to interannual winter climate prediction in southeastern China. Significance Statement The purpose of this study is to better understand how ENSO influences winter surface air temperature in southeastern China. Despite insignificant responses of winter daily maximum temperature to ENSO, we find here a robust ENSO influence on the daily minimum temperature, with warm anomalies tending to occur during El Niño events. Further evidence suggests that this diurnal cycle–dependent ENSO influence is mainly caused by ENSO-induced change in local cloudiness, which has a different radiative heating effect between day and night. Our findings are of great importance for improving regional climate prediction, which will benefit social and economic activities. [ABSTRACT FROM AUTHOR]

Current models for spatial extremes are concerned with the joint upper (or lower) tail of the distribution at two or more locations. Such models cannot account for teleconnection patterns of 2-m surface air temperature (T2m) in North America, where very low temperatures in the contiguous United States may coincide with very high temperatures in Alaska in the wintertime. This dependence between warm and cold extremes motivates the need for a model with opposite-tail dependence in spatial extremes. This work develops a statistical modeling framework that has flexible behavior in all four pairings of high and low extremes at pairs of locations. In particular, we use a mixture of rotations of common Archimedean copulas to capture various combinations of four-corner tail dependence. We study teleconnected T2m extremes using ERA5 of daily average 2-m temperature during the boreal winter. The estimated mixture model quantifies the strength of opposite-tail dependence between warm temperatures in Alaska and cold temperatures in the midlatitudes of North America, as well as the reverse pattern. These dependence patterns are shown to correspond to blocked and zonal patterns of midtropospheric flow. This analysis extends the classical notion of correlation-based teleconnections to considering dependence in higher quantiles. [ABSTRACT FROM AUTHOR]

Modeled global warming is often quantified using global near-surface air temperature (Tas). Meanwhile, long-term temperature datasets combine observations of Tas over land with sea surface temperature (SST) over ocean. Modeled ocean Tas warms more than SST, which can bias model--observation comparisons. Skin temperature (Ts), which is typically warmer than Tas, follows SST changes so the ocean surface temperature discontinuity δTs 5 Ts 2 Tas decreases with warming. Here I show that under CO2 forcing, decreased δTs is consistently simulated for nonpolar ocean within 6608S/N, but not for other regions. I investigate the causes of oceanic dTs decrease using a LongRunMIP climate simulation, radiative kernels, and standard methods for diagnosing forcing and feedbacks from the CMIP5 ensemble. CO2 forcing establishes longwave heating of the lower atmosphere and subsequent adjustments that result in a small Tas increase, and therefore a δTs decrease. During the subsequent warming in response to CO2 forcing, the model-mean surface evaporation feedback is 3.6 W m-2 °C-1 over oceans, which reduces Ts warming relative to Tas and further shrinks δTs. Present-day forcing and feedback contributions are of similar magnitude, and both contribute to small differences in model--observation comparisons of global warming rates when these differences are not accounted for. [ABSTRACT FROM AUTHOR]

A major uncertainty in reconstructing historical sea surface temperature (SST) before the 1990s involves correcting for systematic offsets associated with bucket and engine-room intake temperature measurements. A recent study used a linear scaling of coastal station-based air temperatures (SATs) to infer nearby SSTs, but the physics in the coupling between SATs and SSTs generally gives rise to more complex regional air–sea temperature differences. In this study, an energy-balance model (EBM) of air–sea thermal coupling is adapted for predicting near-coast SSTs from coastal SATs. The model is shown to be more skillful than linear-scaling approaches through cross-validation analyses using instrumental records after the 1960s and CMIP6 simulations between 1880 and 2020. Improved skill primarily comes from capturing features reflecting air–sea heat fluxes dominating temperature variability at high latitudes, including damping high-frequency wintertime SAT variability and reproducing the phase lag between SSTs and SATs. Inferred near-coast SSTs allow for intercalibrating coastal SAT and SST measurements at a variety of spatial scales. The 1900–40 mean offset between the latest SST estimates available from the Met Office (HadSST4) and SAT-inferred SSTs range between −1.6°C (95% confidence interval: [−1.7°, −1.4°C]) and 1.2°C ([0.8°, 1.6°C]) across 10° × 10° grids. When further averaged along the global coastline, HadSST4 is significantly colder than SAT-inferred SSTs by 0.20°C ([0.07°, 0.35°C]) over 1900–40. These results indicate that historical SATs and SSTs involve substantial inconsistencies at both regional and global scales. Major outstanding questions involve the distribution of errors between our intercalibration model and instrumental records of SAT and SST as well as the degree to which coastal intercalibrations are informative of global trends. Significance Statement: To evaluate the consistency of instrumental surface temperature estimates before the 1990s, we develop a coupled energy-balance model to intercalibrate measurements of sea surface temperature (SST) and station-based air temperature (SAT) near global coasts. Our model captures geographically varying physical regimes of air–sea coupling and outperforms existing methods in inferring regional SSTs from SAT measurements. When applied to historical temperature records, the model indicates significant discrepancies between inferred and observed SSTs at both global and regional scales before the 1960s. Our findings suggest remaining data issues in historical temperature archives and opportunities for further improvements. [ABSTRACT FROM AUTHOR]

We develop a statistical method to assess CMIP6 simulations of large-scale surface temperature change during the historical period (1850–2014), considering all time scales, allowing for the different unforced variability of each model and the observations, observational uncertainty, and variable ensemble size. The generality of this method, and the fact that it incorporates information about the unforced variability, makes it a useful model assessment tool. We apply this method to the historical simulations of the CMIP6 multimodel ensemble. We use three indices that measure different aspects of large-scale surface air temperature change: global mean, hemispheric gradient, and a recently developed index that captures the sea surface temperature (SST) pattern in the tropics (SST#; see Fueglistaler and Silvers). We use the following observations: HadCRUT5 for the first two indices, and AMIPII and ERSSTv5 for SST#. In each case, we test the hypothesis that the model's forced response is compatible with the observations, accounting for unforced variability in both models and observations as well as measurement uncertainty. This hypothesis is accepted more often (75% of the models) for the hemispheric gradient than for the global mean, for which half of the models fail the test. The tropical SST pattern is poorly simulated in all models. Given that the tropical SST pattern can strongly modulate the relationship between energy imbalance and global-mean surface temperature anomalies on annual to decadal time scales (short-term feedback parameter), we suggest this should be a focus area for future improvements due to its potential implications for the global-mean temperature evolution in decadal time scales. [ABSTRACT FROM AUTHOR]

The diurnal variations of surface and air temperature are closely related, but their different responses to evaporative conditions can inform us about land–atmosphere interactions. Here, we evaluate the responses of the diurnal ranges in surface (ΔTs) and air (ΔTa) temperature to evaporative fraction at 160 FLUXNET sites and in the ERA5 reanalysis. We show that the sensitivity of ΔTs to evaporative fraction depends on vegetation type, whereas ΔTa does not. On days with low evaporative fraction, ΔTs in FLUXNET is enhanced by up to ∼20 K (∼30 K in ERA5) in short vegetation, but only by up to ∼10 K (∼10 K in ERA5) in forests. Note that ΔTa responds rather similarly to evaporative fraction irrespective of vegetation type (∼5 K in FLUXNET, ∼10 K in ERA5). We find a systematic bias in ERA5's ΔT response to evaporative conditions, showing a stronger sensitivity to evaporative fraction than in FLUXNET. We then demonstrate with a simple atmospheric boundary layer (SABL) model that the weak response of ΔTa to evaporative fraction can be explained by greater boundary layer growth under dry conditions, which increases the heat storage capacity and reduces the response of air temperature to evaporative fraction. Additionally, using a simplified surface energy balance (SSEB) model we show that ΔTs mainly responds to solar radiation, evaporative fraction, and aerodynamic conductance. We conclude that the dominant patterns of diurnal temperature variations can be explained by fundamental physical concepts, which should help us to better understand the main controls of land–atmosphere interactions. Significance Statement: Generally, air temperature is used more widely than the surface temperature, and often they are assumed to be equivalent. However, we show that their responses to changes in vegetation type and evaporative conditions are quite different. Using FLUXNET observations, ERA5 reanalysis, and two simple physical models, we found that these responses are much stronger in surface temperature, especially in short vegetation, and relatively weaker in air temperature. Despite being measured just 2 m above the surface, air temperature carries lesser imprints of evaporation and vegetation than the surface temperature because of boundary layer dynamics. These findings suggest the importance of coupled land–atmosphere processes in shaping surface and air temperature differently and provide insights on their distinctive responses to global changes. [ABSTRACT FROM AUTHOR]

Summer mean (June, July, and August) surface air temperature (SSAT) in East Asia during the period from 1958 to 2001 has shown a warming. However, the relative contributions of external forcing (EF) and internal climate variability (ICV) to the SSAT changes over East Asia remain unclear. In this study, a new approach is applied to estimate the changes in the SSAT determined by the effects of EF and ICV over East Asia during the period from 1958 to 2001. Reanalysis data as well as simulated results from both global atmosphere–ocean coupled model outputs and a regional climate model (RCM) are used for this approach. The observed SSATs over East Asia have undergone a decreasing trend from 1958 to 1972 (20.148C decade-1, p<0.01) and an increasing trend after 1972 (0.248C decade-1, p<0.01). While these features are not captured by the reanalysis studied here, they are reproduced when the reanalysis output is downscaled using an RCM. The effects of the EF and the ICV on the SSAT can be separated based on the RCM downscaling simulation. The results show that the SSAT with EF displayed significant warming over most regions of East Asia, whereas the SSAT with ICV mainly exhibited cooling over East Asia. Furthermore, EF mainly influenced the decadal changes of the SSAT, whereas the ICV mainly influenced the interannual changes in the SSAT over East Asia. The interannual changes of the SSAT over East Asia that were influenced by the ICV are mainly manifested as the combined effects of the large-scale ocean–atmosphere circulations, which expressed 79% explanatory power on the SSAT changes. [ABSTRACT FROM AUTHOR]

Vegetation activity and phenology are significantly affected by climate change, and changes in vegetation activity and phenology can in turn affect regional or global climate patterns. As one of the world’s great biomes, temperate grasslands have undergone remarkable changes in recent decades, but the connections between vegetation activity and phenology changes and regional climate there have remained unclear. Using the observation minus reanalysis (OMR) method, this study investigated the possible effects of vegetation activity and vegetation growing season changes on air temperatures in temperate grasslands of China. The results showed that average NDVI of the temperate grassland significantly increased by 0.011 decade21 for the growing season during 1982–2015. The growing season started earlier and ended later, resulting in an extension. Increased vegetation activity during spring and autumn significantly warmed spring and autumn air temperatures by reducing albedo. By contrast, summer greening had no significant effect on summer temperature, due to the opposing effects of decreased albedo and enhanced evapotranspiration on temperature. The earlier start and later end of the growing season contributed to warmer spring and autumn air temperatures. As phenological changes had no significant effect on summer temperature, the extended growing season warmed air temperature. Our results suggest that the climate change–induced increasing vegetation activity and extended growing seasons can further aggravate regional warming in temperate grasslands of China, implying that the effects of vegetation activity and phenology changes on regional climate should be considered in climate models for accurately simulating climate change in temperate grasslands. [ABSTRACT FROM AUTHOR]

Antarctic sea ice is projected to decrease in response to increasing greenhouse gas concentrations. Limited studies so far have examined the coupled atmosphere–ocean response to Antarctic sea ice loss. Here, we isolate the response to Antarctic sea ice loss in the atmosphere and ocean using bespoke sea ice albedo perturbation experiments with HadGEM3-GC3.1-LL, provide the first detailed examination of the global ocean response, and quantify the importance of atmosphere–ocean coupling, through comparison to uncoupled experiments with prescribed Antarctic sea ice loss. Lower-tropospheric warming and moistening over regions of sea ice loss and the nearby Southern Ocean are simulated in both coupled and uncoupled configurations but are of greater magnitude in the coupled model. A weakening and equatorward shift of the tropospheric westerly jet are simulated in both configurations, but are also larger in the coupled model. Ocean coupling allows the warming response to spread northward, and by poleward atmospheric energy transport, back to the Antarctic interior. Warmer tropical sea surface temperatures enhance atmospheric convection, driving upper-tropospheric warming and triggering atmospheric teleconnections to the extratropics, including a weakened Aleutian low. A 20% reduction in Antarctic Circumpolar Current transport and a weakening of the shallow tropical convergence cell are simulated. Surface waters warm and freshen globally, becoming more stratified and stable in the Southern Ocean, with similar changes, but of lesser magnitude, in the Arctic Ocean, where sea ice declines. Our results suggest that the climate effects of Antarctic sea ice loss stretch from pole to pole and from the heights of the tropical troposphere to the depths of the Southern Ocean. [ABSTRACT FROM AUTHOR]

This study examines the evolution of the interannual warm Arctic–cold continents (WACC) pattern over the North American sector, which refers to the warm Arctic–cold North American pattern (WACNA), and explores its driving mechanism. WACNA features a pair of opposite surface air temperature anomalies centered over the Chukchi–Bering Seas and the North American Great Plains. A negative phase of the warm Arctic–cold Eurasia (WACE) pattern tends to lead a positive phase of the WACNA pattern by about 25 days. Negative Asian–Bering–North American (ABNA)- and Pacific–North American (PNA)-like atmospheric circulation patterns also appear upstream and precede a positive WACNA by about 25 days, gradually develop, reach their peaks when both circulation patterns lead the WACNA by 5 days, and weaken afterward. The negative ABNA-like pattern can be driven by the Siberian snow decline that is related to a negative WACE pattern and its featured Eurasian warming, whereas the negative PNA-like pattern is influenced by negative SST anomalies over the tropical central-eastern Pacific Ocean that resemble the tropical ENSO variability. The surface signatures of both patterns highlight a horseshoe-shaped high pressure anomaly straddling over the Gulf of Alaska, Alaska, and northwestern Canada. The anomalous warm advection from the North Pacific and cold advection from the Arctic that follow the circulation anomalies, as well as sea ice declines over the Chukchi–Bering Seas and growth over Hudson Bay, lead to the formation of the positive WACNA pattern. Processes with circulation anomalies of opposite signs will likewise lead to the negative WACNA pattern. [ABSTRACT FROM AUTHOR]

Key processes associated with the leading intraseasonal variability mode of wintertime surface air temperature (SAT) over Eurasia and the Arctic region are investigated in this study. Characterized by a dipole distribution in SAT anomalies centered over north Eurasia and the Arctic, respectively, and coherent temperature anomalies vertically extending from the surface to 300 hPa, this leading intraseasonal SAT mode and associated circulation have pronounced influences on global surface temperature anomalies including the East Asian winter monsoon region. By taking advantage of realistic simulations of the intraseasonal SAT mode in a global climate model, it is illustrated that temperature anomalies in the troposphere associated with the leading SAT mode are mainly due to dynamic processes, especially via the horizontal advection of winter mean temperature by intraseasonal circulation. While the cloud–radiative feedback is not critical in sustaining the temperature variability in the troposphere, it is found to play a crucial role in coupling temperature anomalies at the surface and in the free atmosphere through anomalous surface downward longwave radiation. The variability in clouds associated with the intraseasonal SAT mode is closely linked to moisture anomalies generated by similar advective processes as for temperature anomalies. Model experiments suggest that this leading intraseasonal SAT mode can be sustained by internal atmospheric processes in the troposphere over the mid- to high latitudes by excluding forcings from Arctic sea ice variability, tropical convective variability, and the stratospheric processes. [ABSTRACT FROM AUTHOR]

A review of many studies published since the late 1920s reveals that the main driving mechanisms responsible for the early-twentieth-century Arctic warming (ETCAW) are not fully recognized. The main obstacle seems to be our limited knowledge about the climate of this period and some forcings. A deeper knowledge based on greater spatial and temporal resolution data is needed. The article provides new (or improved) knowledge about surface air temperature (SAT) conditions (including their extreme states) in the Arctic during the ETCAW. Daily and subdaily data have been used (mean daily air temperature, maximum and minimum daily temperature, and diurnal temperature range). These were taken from 10 individual years (selected from the period 1934–50) for six meteorological stations representing parts of five Arctic climatic regions. Standard SAT characteristics were analyzed (monthly, seasonal, and yearly means), as were rarely investigated aspects of SAT characteristics (e.g., number of characteristic days, day-to-day temperature variability, and the onset, end, and duration of thermal seasons). The results were compared with analogical calculations done for data taken from the contemporary Arctic warming (CAW) period (2007–16). The Arctic experienced warming between the ETCAW and the CAW. The magnitude of warming was greatest in the Pacific (2.7°C) and Canadian Arctic (1.9°C) regions. A shortening of winter and lengthening of summer were noted. Furthermore, the climate was also a little more continental (except the Russian Arctic) and less stable (greater day-to-day variability and diurnal temperature range) during the ETCAW than during the CAW. Significance Statement: It is well established that human activity (particularly increased greenhouse gas emissions) is the primary driving mechanism of the recent dramatic warming in the Arctic. However, the causes of a similar warming here in the first half of the twentieth century remain uncertain. The limited knowledge about the climate of that period—which mainly results from the low resolution of data—is a significant obstacle to a definitive determination of the forcing mechanisms. Therefore, the main aim of our paper is to improve our understanding of specific aspects of weather and climate (including extremes) using long-term series of daily and subdaily data that have rarely been applied for this purpose. This new, more comprehensive knowledge about the historical Arctic climate should allow the scientific community (particularly climate modelers) to better validate both climate models and reanalysis products and, consequently, to more precisely identify the causes of the early-twentieth-century Arctic warming. [ABSTRACT FROM AUTHOR]

Interdecadal variations of the relationship between El Niño–Southern Oscillation (ENSO) and the Indo-China Peninsula (ICP) surface air temperature (SAT) in winter are investigated in the study. Generally, there exists a positive correlation between them during 1958–2015 because the ENSO-induced anomalous western North Pacific anticyclone (WNPAC) is conducive to pronounced temperature advection anomalies over the ICP. However, such correlation is unstable in time, having experienced a high-to-low transition around the mid-1970s and a recovery since the early 1990s. This oscillating relationship is owing to the anomalous WNPAC intensity in different decades. During the epoch of high correlation, the anomalous WNPAC and associated southwesterly winds over the ICP are stronger, which brings amounts of warm temperature advection and markedly heats the ICP. In contrast, a weaker WNPAC anomaly and insignificant ICP SAT anomalies are the circumstances for the epoch of low correlation. It is also found that substantial southwesterly wind anomalies over the ICP related to the anomalous WNPAC occur only when large sea surface temperature (SST) anomalies over the northwest Indian Ocean (NWIO) coincide with ENSO (viz., when the ENSO–NWIO SST connection is strong). The NWIO SST anomalies are capable of driving favorable atmospheric circulation that effectively alters ICP SAT and efficiently modulates the ENSO–ICP SAT correlation, which is further supported by numerical simulations utilizing the Community Atmospheric Model, version 4 (CAM4). This paper emphasizes the non-stationarity of the ENSO–ICP SAT relationship and also uncovers the underlying modulation factors, which has important implications for the seasonal prediction of the ICP temperature. [ABSTRACT FROM AUTHOR]

This study evaluates the performance of models from phase 5 and phase 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6) by comparing feedbacks in models with those inferred from observations. Overall, we find no systematic disagreements between the feedbacks in the model ensembles and feedbacks inferred from observations, although there is a wide range in the ability of individual models to reproduce the observations. In particular, 40 of 52 models have best estimates that fall within the uncertainty of the observed total feedback. We quantify two sources of uncertainty in the model ensembles: 1) the structural difference, due to the differences in model parameterizations, and 2) the unforced pattern effect, due to unforced variability, and find that both are important when comparing with an 18-yr observational dataset. We perform the comparison using two energy balance frameworks: the traditional energy balance framework, in which it is assumed that changes in energy balance are controlled by changes in global average surface temperatures, and an alternative framework that assumes the changes in energy balance are controlled by tropical atmospheric temperatures. We find that the alternative framework provides a more robust way of comparing the models with observations, with both smaller structural differences and smaller unforced pattern effect. However, when considering the relation of feedbacks in response to interannual variability and long-term warming, the traditional framework has advantages. There are no great differences between the CMIP5 and CMIP6 ensembles' ability to reproduce the observed feedbacks. [ABSTRACT FROM AUTHOR]

The effect of Eurasian spring snowmelt on surface air temperature (SAT) in late spring (April-May) and early summer (June-July) and the relevant physical mechanisms during 1981-2016 are investigated. Results show that the first mode of the interannual Eurasian spring snowmelt represents an east-west dipole anomaly pattern, with an intense center over Siberia and another moderate center around eastern Europe. The European spring snowmelt shows an insignificant relation to the local SAT, whereas the Siberian spring snowmelt has a significant impact on the SAT in late spring and early summer. More Siberian spring snowmelt contributes to higher SAT in late spring and lower SAT in early summer via different mechanisms. In late spring, increased Siberian spring snowmelt corresponds to less local surface albedo and cloud cover, leading to the surface absorbing more shortwave radiation and thereby higher SAT. The subsurface and deep soil moisture anomalies generated from Siberian spring snowmelt can persist into early summer. Excessive Siberian spring snowmelt corresponds to positive soil moisture anomalies, contributing to decreased sensible heat and increased cloud cover in early summer. Increased cloud cover leads to the surface receiving less shortwave radiation. Thus, lower SAT appears over Siberia in early summer due to reduced sensible heat and shortwave radiation. However, the simulation of Eurasian spring snowmelt variability and its influences on SAT via the snow hydrological effect is still a challenge for the climate models that participated in phase 6 of the Coupled Model Intercomparison Project. [ABSTRACT FROM AUTHOR]

Superimposed on a warming trend, Arctic winter surface air temperature (SAT) exhibits substantial interannual variability, the underlying mechanisms of which are unclear, especially with regard to the role of sea ice variations and atmospheric processes. Here, atmospheric reanalysis data and idealized atmospheric model simulations are used to reveal the mechanisms by which sea ice variations and atmospheric anomalous conditions affect interannual variations in wintertime Arctic SAT. Results show that near-surface interannual warming in the Arctic is accompanied by comparable warming throughout large parts of the Arctic troposphere and large-scale anomalous atmospheric circulation patterns. Within the Arctic, changes in large-scale atmospheric circulations due to internal atmospheric variability explain a substantial fraction of interannual variation in SAT and tropospheric temperatures, which lead to an increase in moisture and downward longwave radiation, with the rest likely coming from sea ice–related and other surface processes. Arctic winter sea ice loss allows the ocean to release more heat and moisture, which enhances Arctic warming; however, this effect on SAT is confined to the ice-retreat area and has a limited influence on large-scale atmospheric circulations. [ABSTRACT FROM AUTHOR]