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Past versions of global surface temperature (ST) datasets have been shown to have underestimated the recent warming trend over 1998–2012. This study uses a newly updated global land surface air temperature and a land and marine surface temperature dataset, referred to as China global land surface air temperature (C-LSAT) and China merged surface temperature (CMST), to estimate trends in the global mean ST (combining land surface air temperature and sea surface temperature anomalies) with the data uncertainties being taken into account. Comparing with existing datasets, the statistical significance of the global mean ST warming trend during the past century (1900–2017) remains unchanged, while the recent warming trend during the “hiatus” period (1998–012) increases obviously, which is statistically significant at 95% level when fitting uncertainty is considered as in previous studies (including IPCC AR5) and is significant at 90% level when both fitting and data uncertainties are considered. Our analysis shows that the global mean ST warming trends in this short period become closer among the newly developed global observational data (CMST), remotely sensed/Buoy network infilled datasets, and reanalysis data. Based on the new datasets, the warming trends of global mean land SAT as derived from C-LSAT 2.0 for the period of 1979–2019, 1951–2019, 1900–2019 and 1850–2019 were estimated to be 0.296, 0.219, 0.119 and 0.081 °C/decade, respectively. The warming trends of global mean ST as derived from CMST for the periods of 1998–2019, 1979–2019, 1951–2019 and 1900–2019 were estimated to be 0.195, 0.173, 0.145 and 0.091 °C/decade, respectively.

Based on the 1979–2018 datasets of Climate Prediction Center (CPC) daily maximum air temperature, HadISST, and NCEP-DOE II reanalysis, the impact of Pacific decadal oscillation (PDO) and Atlantic multidecadal oscillation (AMO) on the interdecadal variability in extreme high temperature (EHT) in North China (NC) is investigated through observational analysis and National Center for Atmospheric Research (NCAR) Community Atmosphere Model version 5.3 (CAM5.3) numerical simulations. The observational results show an interdecadal shift in NC’s EHT in approximately 1996 with a cold period from 1983 to 1996 and a warm period from 1997 to 2014. The summer PDO and AMO are both closely related to NC’s EHT, of which AMO dominates. From the cold to warm period, the combination of PDO and AMO changed from a positive PDO (+ PDO) phase and a negative AMO (− AMO) phase to a negative PDO (− PDO) phase and a positive AMO (+ AMO) phase. The shift in the antiphase combination of PDO and AMO plays an important role in the interdecadal transition of NC’s EHT in 1996. PDO could impact NC’s EHT through the Pacific-East Asia teleconnection pattern, and AMO could influence the NC’s EHT through an atmospheric wave train in the midlatitudes of the Northern Hemisphere. During the warm period (− PDO and + AMO), warmer sea surface temperature anomalies (SSTA) in the northern North Pacific (NP) and North Atlantic (NA) could cause anticyclonic circulation anomalies over these two basins. The anticyclonic circulations anomalies over the NP could enhance the anticyclone over NC through the Pacific-East Asian (PEA) teleconnection pattern. It could also cause an easterly wind from the NP to NC which would weaken the upper westerly over NC. The anticyclonic anomalies over the NA, which were parts of the wave train, could affect other sectors of the wave train, resulting in anticyclonic anomalies over NC. The anticyclonic anomalies over NC could strengthen the continental high and weaken the upper zonal westerly, resulting in favorable EHT conditions. During the cold period (+ PDO and − AMO), because of the same atmospheric response mechanism, a westerly wind from NC to NP and a wave train with reversed anomaly centers could be found, causing a cyclonic anomaly over NC that is not conducive to the EHT. A series of numerical simulations using CAM5.3 confirm the above observational results and show that the combination of + PDO and − AMO changing to − PDO and + AMO has a great impact on the interdecadal shift in EHT in NC in 1996. The simulations also show that both + AMO and − PDO can lead the EHT in NC individually, and the impact of AMO on the EHT in NC is dominant.

In the summer (July and August) of 2022, unprecedented heat wave occurred along the Yangtze River Valley (YRV) over East Asia while unprecedented flood occurred over western South Asia (WSA), which are located on the eastern and western sides of Tibetan Plateau (TP). Here, by analyzing the interannual variability based on observational and reanalysis data, we show evidences that the anomalous zonal flow over subtropical Tibetan Plateau (TP) explains a major fraction the extreme events occurred in 2022. As isentropic surfaces incline eastward (westward) with altitude on the eastern (western) side of the warm center over TP in summer, anomalous easterly (westerly) flow in upper troposphere generates anomalous descent (ascent) on the eastern side of TP and anomalous ascent (descent) on the western side of TP via isentropic gliding. The anomalous easterly flow is extremely strong to reverse the climatological westerly flow over subtropical TP in 1994, 2006, 2013 and 2022. The easterly flow in 2022 is the strongest since 1979, and it generates unprecedented descent (ascent) anomaly on the eastern (western) side of TP, leading to extreme heat wave over YRV and extreme flood over WSA in 2022. The anomalously strong easterly flow over subtropical TP in 2022 is dominated by atmospheric internal variability related to mid-latitude wave train, while the cold sea surface temperature anomaly over the tropical Indian Ocean increases the probability of a reversed zonal flow over TP by reducing the meridional gradient of tropospheric temperature.

Over the last century, the global mean surface air temperature (SAT) has experienced two periods of warming slowdown (hiatuses), namely 1940–1975 and 1998–2012, as well as showing well-defined interdecadal oscillations. Previous studies have focused mainly on the most recent hiatus, and little is known about the period between 1940 and 1975. From the point of view of the sea surface temperature (SST), there are two aspects of interest; i.e., the climatological SST and SST variability. In this paper, observational and modelling evidence is used to show that, compared with the climatological SST, SST variability has been the main cause of the slowdown in rate of increase in SAT since 1940. In addition, the observational data and simulation results show that SST variability had a greater impact on the slowdown in rate of increase in SAT from 1940 to 1975 (− 1.2 × 10 −3  °C/year) than from 1998 to 2012 (− 5.7 × 10 −3  °C/year). The SAT change over the period 1940–1975 (1.0 × 10 −4  °C/year) was less affected by the climatological SST forcing experiment than that over the period 1998–2012 (− 5.0 × 10 −4  °C/year). Comparing with 1940–1975, the SAT change over the period 1998–2012 was much affected by the global SAT long-term warming. The distributions of wind stress and atmospheric pressure both indicate that, although the eastern Pacific Ocean played an important role in influencing the global SAT trend between 1998 and 2012, it made little contribution to changes in global SAT between 1940 and 1975. In addition, from the perspective of seasonality, the interdecadal variation of SAT over these two periods was a seasonally dependent phenomenon. Over the period 1940–1975, the annual SAT trend essentially followed the summer SAT trend, whereas between 1998 and 2012, winter was the dominant season of annual SAT change.

Marine heatwaves (MHWs) are periods of extreme warm sea surface temperature that persist for days to months 1 and can extend up to thousands of kilometres 2 . Some of the recently observed marine heatwaves revealed the high vulnerability of marine ecosystems 3 – 11 and fisheries 12 – 14 to such extreme climate events. Yet our knowledge about past occurrences 15 and the future progression of MHWs is very limited. Here we use satellite observations and a suite of Earth system model simulations to show that MHWs have already become longer-lasting and more frequent, extensive and intense in the past few decades, and that this trend will accelerate under further global warming. Between 1982 and 2016, we detect a doubling in the number of MHW days, and this number is projected to further increase on average by a factor of 16 for global warming of 1.5 degrees Celsius relative to preindustrial levels and by a factor of 23 for global warming of 2.0 degrees Celsius. However, current national policies for the reduction of global carbon emissions are predicted to result in global warming of about 3.5 degrees Celsius by the end of the twenty-first century 16 , for which models project an average increase in the probability of MHWs by a factor of 41. At this level of warming, MHWs have an average spatial extent that is 21 times bigger than in preindustrial times, last on average 112 days and reach maximum sea surface temperature anomaly intensities of 2.5 degrees Celsius. The largest changes are projected to occur in the western tropical Pacific and Arctic oceans. Today, 87 per cent of MHWs are attributable to human-induced warming, with this ratio increasing to nearly 100 per cent under any global warming scenario exceeding 2 degrees Celsius. Our results suggest that MHWs will become very frequent and extreme under global warming, probably pushing marine organisms and ecosystems to the limits of their resilience and even beyond, which could cause irreversible changes. Satellite observations and Earth system model simulations reveal that marine heatwaves have increased in recent decades and will increase further in terms of frequency, intensity, duration and spatial extent.

A global land–ocean temperature record has been created by combining the Berkeley Earth monthly land temperature field with spatially kriged version of the HadSST3 dataset. This combined product spans the period from 1850 to present and covers the majority of the Earth's surface: approximately 57 % in 1850, 75 % in 1880, 95 % in 1960, and 99.9 % by 2015. It includes average temperatures in 1∘×1∘ lat–long grid cells for each month when available. It provides a global mean temperature record quite similar to records from Hadley's HadCRUT4, NASA's GISTEMP, NOAA's GlobalTemp, and Cowtan and Way and provides a spatially complete and homogeneous temperature field. Two versions of the record are provided, treating areas with sea ice cover as either air temperature over sea ice or sea surface temperature under sea ice, the former being preferred for most applications. The choice of how to assess the temperature of areas with sea ice coverage has a notable impact on global anomalies over past decades due to rapid warming of air temperatures in the Arctic. Accounting for rapid warming of Arctic air suggests ∼ 0.1 ∘C additional global-average temperature rise since the 19th century than temperature series that do not capture the changes in the Arctic. Updated versions of this dataset will be presented each month at the Berkeley Earth website (http://berkeleyearth.org/data/, last access: November 2020), and a convenience copy of the version discussed in this paper has been archived and is freely available at https://doi.org/10.5281/zenodo.3634713 (Rohde and Hausfather, 2020).

The monthly Extended Reconstructed Sea Surface Temperature (ERSST) dataset, available on global 2° × 2° grids, has been revised herein to version 4 (v4) from v3b. Major revisions include updated and substantially more complete input data from the International Comprehensive Ocean–Atmosphere Data Set (ICOADS) release 2.5; revised empirical orthogonal teleconnections (EOTs) and EOT acceptance criterion; updated sea surface temperature (SST) quality control procedures; revised SST anomaly (SSTA) evaluation methods; updated bias adjustments of ship SSTs using the Hadley Centre Nighttime Marine Air Temperature dataset version 2 (HadNMAT2); and buoy SST bias adjustment not previously made in v3b. Tests show that the impacts of the revisions to ship SST bias adjustment in ERSST.v4 are dominant among all revisions and updates. The effect is to make SST 0.1°–0.2°C cooler north of 30°S but 0.1°–0.2°C warmer south of 30°S in ERSST.v4 than in ERSST.v3b before 1940. In comparison with the Met Office SST product [the Hadley Centre Sea Surface Temperature dataset, version 3 (HadSST3)], the ship SST bias adjustment in ERSST.v4 is 0.1°–0.2°C cooler in the tropics but 0.1°–0.2°C warmer in the midlatitude oceans both before 1940 and from 1945 to 1970. Comparisons highlight differences in long-term SST trends and SSTA variations at decadal time scales among ERSST.v4, ERSST.v3b, HadSST3, and Centennial Observation-Based Estimates of SST version 2 (COBE-SST2), which is largely associated with the difference of bias adjustments in these SST products. The tests also show that, when compared with v3b, SSTAs in ERSST.v4 can substantially better represent the El Niño/La Niña behavior when observations are sparse before 1940. Comparisons indicate that SSTs in ERSST.v4 are as close to satellite-based observations as other similar SST analyses.

Global radiative feedbacks have been found to vary in global climate model (GCM) simulations. Atmospheric GCMs (AGCMs) driven with historical patterns of sea surface temperatures (SSTs) and sea ice concentrations produce radiative feedbacks that trend toward more negative values, implying low climate sensitivity, over recent decades. Freely evolving coupled GCMs driven by increasing CO₂ produce radiative feedbacks that trend toward more positive values, implying increasing climate sensitivity, in the future. While this time variation in feedbacks has been linked to evolving SST patterns, the role of particular regions has not been quantified. Here, a Green’s function is derived from a suite of simulations within an AGCM (NCAR’s CAM4), allowing an attribution of global feedback changes to surface warming in each region. The results highlight the radiative response to surface warming in ascent regions of the western tropical Pacific as the dominant control on global radiative feedback changes. Historical warming from the 1950s to 2000s preferentially occurred in the western Pacific, yielding a strong global outgoing radiative response at the top of the atmosphere (TOA) and thus a strongly negative global feedback. Long-term warming in coupled GCMs occurs preferentially in tropical descent regions and in high latitudes, where surface warming yields small global TOA radiation change but large global surface air temperature change, and thus a less-negative global feedback. These results illuminate the importance of determining mechanisms of warm pool warming for understanding how feedbacks have varied historically and will evolve in the future.

The Pacific decadal oscillation (PDO), the dominant year-round pattern of monthly North Pacific sea surface temperature (SST) variability, is an important target of ongoing research within themeteorological and climate dynamics communities and is central to the work of many geologists, ecologists, natural resource managers, and social scientists. Research over the last 15 years has led to an emerging consensus: the PDO is not a single phenomenon, but is instead the result of a combination of different physical processes, including both remote tropical forcing and local North Pacific atmosphere–ocean interactions, which operate on different time scales to drive similar PDO-like SST anomaly patterns. How these processes combine to generate the observed PDO evolution, including apparent regime shifts, is shown using simple autoregressive models of increasing spatial complexity. Simulations of recent climate in coupled GCMs are able to capture many aspects of the PDO, but do so based on a balance of processes often more independent of the tropics than is observed. Finally, it is suggested that the assessment of PDO-related regional climate impacts, reconstruction of PDO-related variability into the past with proxy records, and diagnosis of Pacific variability within coupled GCMs should all account for the effects of these different processes, which only partly represent the direct forcing of the atmosphere by North Pacific Ocean SSTs.

The impact of sea surface temperature anomalies (SSTAs) over the North Pacific (32°–45° N, 140° E–150° W) and North Atlantic (north: 52°–68° N, 60°–20° W; south: 0°–30° N, 100°–40° W) on the summer surface air temperature (SAT) over the Mongolian Plateau (MP) is studied using NCEP/NCAR and Climatic Research Unit (CRU) reanalysis data. The results show that the circumglobal teleconnection (CGT) wave train related to the SSTAs in the North Atlantic propagates along with the westerly jet, resulting in a geopotential height anomaly at 200 hPa that favors an SAT anomalies (SATAs) on the MP. In addition, an anticyclonic (cyclonic) circulation anomaly with the characteristics of an atmospheric ultralong wave at 200 hPa over the Eurasia–Pacific region associated with the SSTAs in the North Pacific is also responsible for the positive (negative) SATAs on the MP. The results further reveal that the SSTAs in the North Pacific and the northern North Atlantic act synergistically on the SATAs on the MP. If there are strongly positive (negative) SSTAs in the North Pacific and the northern North Atlantic at the same time, the probability of a strongly positive (negative) SATAs on the MP is 67% (100%) for the research period of this paper. However, if the strongly positive (negative) SSTAs only appear in the North Pacific or the northern North Atlantic, the probability of a strongly positive (negative) SATAs on the MP is less than 34% (31%). The synergism of the SSTAs in the North Pacific and the northern North Atlantic enhances Rossby wave energy in Eurasia, with more Rossby wave energy spreading to the MP that in turn causes the circulation anomaly on the MP. Meanwhile, baroclinic conditions at 850 hPa north of the North Pacific, the northern and southern North Atlantic favor a northward shift of the westerly jet that guides the Rossby wave downstream so that the circulation anomaly that produces the SATAs on the MP is located in the mid–high latitudes.