Global Mean Temperature Trends Research Articles

Limited reversal of regional climate signals in overshoot scenarios

Without stringent reductions in emission of greenhouse gases in the coming years, an exceedance of the 1.5 °C temperature limit is increasingly likely. This has given rise to so-called temperature overshoot scenarios, in which the global mean surface air temperature exceeds a certain limit (i.e. 1.5 °C above pre-industrial levels) before bringing temperatures back below that limit. Despite their prominence in the climate mitigation literature, the implications of an overshoot for local climate impacts is still understudied. Here we present a comprehensive analysis of implications of an overshoot for regional temperature and precipitation changes as well as climate extremes indices. Based on a multi-model comparison from the Coupled Model Intercomparison Project we find that temperature changes are largely reversible in many regions, but also report significant land–ocean and latitudinal differences after an overshoot. For precipitation, the emerging picture is less clear. In many regions the drying or wetting trend is continued throughout the overshoot irrespective of a change in the global mean temperature trend with resulting consequences for extreme precipitation. Taken together, our results indicate that even under a reversal of global mean temperature increase, regional climate changes may only be partially reversed in the decades after peak warming. We thus provide further evidence that overshooting of a warming level implies considerable risks on the regional level.

Effects of atmospheric aerosols on heat stress over South Asia

The recent trend in global mean temperature is expected to increase the frequency, duration, and intensity of heat waves and heat stress all around the world, especially over the Indian subcontinent. To investigate the plausible mechanisms and implications of meteorological feedback of aerosol forcing on heat stress over South Asia, simulations using a regional climate model (RegCM4) coupled with aerosols were carried out from 2015 to 2019. Generally, extreme heat days are observed mainly over the central and western Indo-Gangetic plains (IGPs) during May. The two heat-humidity indices, wet-bulb temperature (WBT) and heat index (HI), showed moderate effects due to aerosol forcing despite the high aerosol loading during the pre-monsoon. The inclusion of aerosols leads to surface cooling (a reduction in maximum surface temperature), with the highest impact over western India (WI) and the IGP. However, this surface cooling due to aerosols is compensated by an increase in near-surface relative humidity (RH), leading to an increase in WBT and HI. This compensating effect of RH on WBT and HI is greater in WI than that in eastern India. Regional heterogeneity in aerosol-induced changes in heat stress has a strong dependence on land-atmosphere interactions. This study clearly shows that aerosol-induced changes in RH play a decisive role in the assessment of heat stress, which answers the link between the prevalence of high heat stress conditions despite high aerosol loading (surface cooling) over the Indian region.

Emergent Constraints on CMIP6 Climate Warming Projections: Contrasting Cloud- and Surface Temperature–Based Constraints

AbstractThe latest Coupled Model Intercomparison Project (CMIP6) multimodel ensemble shows a broader range of projected warming than the previous-generation CMIP5 ensemble. We show that the projected warming is well correlated with tropical and subtropical low-level cloud properties. These physically meaningful relations enable us to use observed cloud properties to constrain future climate warming. We develop multivariate linear regression models with metrics selected from a set of potential constraints based on a stepwise selection approach. The resulting linear regression model using two low-cloud metrics shows better cross-validated results than regression models that use single metrics as constraints. Application of a regression model using the low-cloud metrics to climate projections results in similar estimates of the mean, but substantially narrower uncertainty ranges, of projected twenty-first-century warming when compared with unconstrained simulations. The resulting projected global-mean warming in 2081–2100 relative to 1995–2014 is 2.84–5.12 K (5%–95% range) for Shared Socioeconomic Pathway (SSP) 5–8.5 compared with a range of 2.34–5.81 K for unconstrained projections, and 0.60–1.70 K for SSP1–2.6 compared to an unconstrained range of 0.38–2.04 K. We provide evidence for a higher lower bound of the projected warming range than that obtained from constrained projections based on the past global-mean temperature trend. Consideration of the impact of the sea surface temperature pattern effect on the recent observed warming trend, which is not well captured in the CMIP6 ensemble, indicates that the relatively low projected warming resulting from the global-mean temperature trend constraint may not be reliable and provides further justification for the use of climatologically based cloud metrics to constrain projections.

Emergent constraints on future precipitation changes.

Future projections of global mean precipitation change (ΔP) based on Earth-system models have larger uncertainties than projections of global mean temperature changes (ΔT)1. Although many observational constraints on ΔT have been proposed, constraints on ΔP have not been well studied2-5 and are often complicated by the large influence of aerosols on precipitation4. Here we show that the upper bound (95th percentile) of ΔP (2051-2100 minus 1851-1900, percentage of the 1980-2014 mean) is lowered from 6.2 per cent to 5.2-5.7 per cent (minimum-maximum range of sensitivity analyses) under a medium greenhouse gas concentration scenario. Our results come from the Coupled Model Intercomparison Project phase 5 and phase 6 ensembles6-8, in which ΔP for 2051-2100 is well correlated with the global mean temperature trends during recent decades after 1980 when global anthropogenic aerosol emissions were nearly constant. ΔP is also significantly correlated with the recent past trends in precipitation when we exclude the tropical land areas with few rain-gauge observations. On the basis of these significant correlations and observed trends, the variance of ΔP is reduced by 8-30 per cent. The observationally constrained ranges of ΔP should provide further reliable information for impact assessments.

On the response of the middle atmosphere to anthropogenic forcing.

Anthropogenic forcing of the atmosphere by greenhouse gases (GHG) and ozone-depleting substances has provided an unintended test of the robustness of current understanding of the physics and chemistry of the middle atmosphere, that is, the stratosphere and mesosphere. We explore this topic by examining how well anthropogenic changes can be simulated by modern, comprehensive numerical models. Specifically, we discuss the simulations of trends in global mean temperature; the development of the ozone hole and its impact on the dynamics of the Southern Hemisphere, both in the stratosphere and troposphere; trends in the stratospheric Brewer-Dobson circulation; and the response of the quasi-biennial oscillation (QBO) to increasing burdens of CO2 . We find that, in most of these cases, numerical simulation is able to reproduce observed changes and provide physical insights into the relevant mechanisms. Simulation of the QBO is on a less firm footing. Although many numerical models can now generate realistic QBOs, future projections of its behavior under the increasing burdens of GHG are inconsistent and even contradictory.

Canadian Continental-Scale Hydrology under a Changing Climate: A Review

Canada, like other high latitude cold regions on Earth, is experiencing some of the most accelerated and intense warming resulting from global climate change. In the northern regions, Arctic amplification has resulted in warming two to three times greater than global mean temperature trends. Unprecedented warming is matched by intensification of wet and dry regions and hydroclimatic cycles, which is altering the spatial and seasonal distribution of surface waters in Canada. Diagnosing and tracking hydrologic change across Canada requires the implementation of continental-scale prediction models owing the size of Canada’s drainage basins, their distribution across multiple eco- and climatic zones, and the scarcity and paucity of observational networks. This review examines the current state of continental-scale climate change across Canada and the anticipated impacts to freshwater availability, including the role of anthropogenic regulation. The review focuses on continental and regional-scale prediction that underpins operational design and long-term resource planning and management in Canada. While there are significant process-based changes being experienced within Canadian catchments that are equally—if not more so—critical for community water availability, the focus of this review is on the cumulative effects of climate change and anthropogenic regulation for the Canadian freshwater supply.

Long‐Term Variability and Tendencies in Middle Atmosphere Temperature and Zonal Wind From WACCM6 Simulations During 1850–2014

AbstractLong‐term variability of middle atmosphere temperature (T) and zonal wind (U) is investigated using a three‐member ensemble of historical simulations of NCAR's Whole Atmospheric Community Climate Model latest version 6 (WACCM6) for 1850–2014 (165 years). The model reproduces the climatological features of T and U. The contributions of Quasi Biennial Oscillation (QBO) at 10 and 30 hPa, solar cycle (SC), El Niño‐Southern Oscillation (ENSO), ozone depleting substances (ODS), carbon dioxide (CO2), and stratospheric sulfate aerosol (volcanic eruptions) to change in monthly zonal mean T and U are analyzed using multiple linear regression. The signal due to CO2 increase dominates as a predictor of the net multidecadal global annual mean temperature change at all levels in the middle atmosphere. Contributions from ODS also affect the net multidecadal global mean temperature trend in the stratosphere. Because of similarities in the time evolution of the emissions of CO2 and ODS, the analysis of existing model output cannot accurately separate the attributions of cooling to these two dominant forcing processes. On shorter time scales, solar flux variations are the largest source of variability in the mesosphere while volcanic eruptions are the largest in the stratosphere. In the stratosphere and mesosphere, both QBO and ENSO can significantly impact zonal mean temperature and zonal‐mean zonal wind depending on latitudes, but their impact on the multidecadal global mean temperature trend is very small.

Urbanization effects on surface air temperature trends in Thailand during 1970-2019

Continued urban expansion undergone in the last decades has converted many weather stations in Thailand into suburban and urban setting. Based on homogenized data during 1970-2019, therefore, this study examines urbanization effects on mean surface air temperature (Tmean) trends in Thailand. Analysis shows that urban-type stations register the strongest warming trends while rural-type stations exhibit the smallest trends. Across Thailand, annual urban-warming contribution exhibits a wide range (< 5% to 77%), probably manifesting the Urban Heat Island (UHI) differences from city to city resulting from the varied urban characteristics and climatic background. Country-wide average urban warming contribution shows a significant increasing trend of 0.15 <sup>o</sup>C per decade, accounting for 40.5% of the overall warming. This evidence indicates that urban expansion has great influence on surface warming, and the urban-warming bias contributes large fraction of rising temperature trends in Thailand. The increasing trend of annual Tmean for Thailand as a whole after adjusting urban-warming bias is brought down to the same rate as the annual global mean temperature trend, reflecting a national baseline signal driven by large-scale anthropogenic-induced climate change. Our results provide a scientific reference for policy makers and urban planners to mitigate substantial fraction of the UHI warming.

Crossbreeding CMIP6 Earth System Models With an Emulator for Regionally Optimized Land Temperature Projections

AbstractThe newest generation of the Coupled Model Intercomparison Project (CMIP6) exhibits a larger spread in temperature projections at the end of the 21st century than the previous generation. Here, a modular Earth System Model emulator is used to evaluate the realism of the warming signal in CMIP6 models on both global and regional scales, by comparing their global trends and regional response parameters to observations. Subsequently, the emulator is employed to derive large “crossbred” multimodel initial‐condition ensembles of regionally optimized land temperature projections by combining observationally constrained global mean temperature trend trajectories with observationally constrained local parameters. In the optimized ensembles, the warmest temperature projections are generally reduced and for the coolest projections both higher and lower values are found, depending on the region. The median shows less changes in large parts of the globe. These regional differences highlight the importance of a geographically explicit evaluation of Earth System Model projections.

Climate Model Projections of 21st Century Global Warming Constrained Using the Observed Warming Trend

AbstractThe Coupled Model Intercomparison Project Phase 6 (CMIP6) archive includes larger ensembles, longer historical simulations, and models with a broader range of climate sensitivity than CMIP5. These features favor the application of observationally constrained climate projections. The 1970–2014 trend in global mean temperature is well‐correlated with projected future warming across the CMIP6 multimodel ensemble. We first evaluate an approach that weights simulations based on the realism and degree of independence of their 1970–2014 trends, by treating each historical simulation in turn as pseudo‐observations, and using the other models and weighting method to predict 21st century warming in the model concerned. The method performs well based on correlation and probabilistic measures. Applying the method using the observed 1970–2014 warming trend results in only small changes in the mean and lower bound of CMIP6 projected warming but substantially reduces the upper bound of projected early‐, mid‐ and late‐21st century warming under all SSP scenarios.

The dependence of the northern extratropical climate response to external forcing on the phase of Atlantic Multidecadal Variability

The extent to which decadal-to-multidecadal climate trends forced by carbon dioxide ( $$\text{CO}_2$$ ) and anthropogenic aerosol (AER) emissions depend on the phase and amplitude of internal modes of climate variability, such as Atlantic Multidecadal Variability (AMV), is an open question. This study uses a fully coupled CMIP5-era general circulation model (GCM) to investigate climate trends forced by increasing $$\text{CO}_2$$ and AER in the presence of opposite decaying phases of the AMV. Ensembles of simulations are initialized from extreme warm ( $$\text{AMV}_{(+)}$$ ) and cold ( $$\text{AMV}_{(-)}$$ ) phases of AMV and, while the global mean temperature trends are similar, significant regional differences are found over the Arctic and northern extratropics. Specifically, the response to $$\text{CO}_2$$ forcing is hemispherically asymmetric, with western Eurasia warming 20–30% more, and North America and the extratropical North Pacific warming 20–30% less, in $$\text{AMV}_{(+)}$$ than in $$\text{AMV}_{(-)}$$ . This asymmetry is explained by the atmospheric response to differences in the initial concentration of sea ice in the Atlantic Arctic sector, and by a large-scale atmospheric teleconnection pattern originating in the tropical Indo-Pacific. A decomposition of the temperature trends reveals that the AMV influence occurs mostly through atmospheric dynamics; however, thermodynamic processes are important in regions of sea ice change, western Eurasia, and eastern North America. The difference in the responses to $$\text{CO}_2$$ and AER forcing between AMV phases reveals that some aspects of the AMV modulation of the response, such as a more positive (negative) temperature trend in $$\text{AMV}_{(+)}$$ than in $$\text{AMV}_{(-)}$$ in western Eurasia (the extratropical North Pacific), are largely independent of the sign, magnitude and spatial pattern of external forcing.

Indian Ocean corals reveal crucial role of World War II bias for twentieth century warming estimates

The western Indian Ocean has been warming faster than any other tropical ocean during the 20th century, and is the largest contributor to the global mean sea surface temperature (SST) rise. However, the temporal pattern of Indian Ocean warming is poorly constrained and depends on the historical SST product. As all SST products are derived from the International Comprehensive Ocean-Atmosphere dataset (ICOADS), it is challenging to evaluate which product is superior. Here, we present a new, independent SST reconstruction from a set of Porites coral geochemical records from the western Indian Ocean. Our coral reconstruction shows that the World War II bias in the historical sea surface temperature record is the main reason for the differences between the SST products, and affects western Indian Ocean and global mean temperature trends. The 20th century Indian Ocean warming pattern portrayed by the corals is consistent with the SST product from the Hadley Centre (HadSST3), and suggests that the latter should be used in climate studies that include Indian Ocean SSTs. Our data shows that multi-core coral temperature reconstructions help to evaluate the SST products. Proxy records can provide estimates of 20th century SST that are truly independent from the ICOADS data base.

Revisiting Whether Recent Surface Temperature Trends Agree with the CMIP5 Ensemble

Abstract In an earlier study, a weaker trend in global mean temperature over the past 15 years relative to the preceding decades was characterized as significantly lower than those contained within the phase 5 of the Coupled Model Intercomparison Project (CMIP5) ensemble. In this study, divergence between model simulations and observations is estimated using a fixed-intercept linear trend with a slope estimator that has one-third the noise variance compared to simple linear regression. Following the approach of the earlier study, where intermodel spread is used to assess the distribution of trends, but using the fixed-intercept trend metric demonstrates that recently observed trends in global mean temperature are consistent () with the CMIP5 ensemble for all 15-yr intervals of observation–model divergence since 1970. Significant clustering of global trends according to modeling center indicates that the spread in CMIP5 trends is better characterized using ensemble members drawn across models as opposed to using ensemble members from a single model. Despite model–observation consistency at the global level, substantial regional discrepancies in surface temperature trends remain.

The contribution of greenhouse gases to the recent slowdown in global-mean temperature trends

The recent slowdown in the rate of increase in global-mean surface temperature (GMST) has generated extensive discussion, but little attention has been given to the contribution of time-varying trends in greenhouse gas concentrations. We use a simple model approach to quantify this contribution. Between 1985 and 2003, greenhouse gases (including well-mixed greenhouse gases, tropospheric and stratospheric ozone, and stratospheric water vapour from methane oxidation) caused a reduction in GMST trend of around 0.03–0.05 K decade−1 which is around 18%–25% of the observed trend over that period. The main contributors to this reduction are the rapid change in the growth rates of ozone-depleting gases (with this contribution slightly opposed by stratospheric ozone depletion itself) and the weakening in growth rates of methane and tropospheric ozone radiative forcing. Although CO2 is the dominant greenhouse gas contributor to GMST trends, the continued increase in CO2 concentrations offsets only about 30% of the simulated trend reduction due to these other contributors. These results emphasize that trends in non-CO2 greenhouse gas concentrations can make significant positive and negative contributions to changes in the rate of warming, and that they need to be considered more closely in analyses of the causes of such variations.

A new statistical approach to climate change detection and attribution

We propose here a new statistical approach to climate change detection and attribution that is based on additive decomposition and simple hypothesis testing. Most current statistical methods for detection and attribution rely on linear regression models where the observations are regressed onto expected response patterns to different external forcings. These methods do not use physical information provided by climate models regarding the expected response magnitudes to constrain the estimated responses to the forcings. Climate modelling uncertainty is difficult to take into account with regression based methods and is almost never treated explicitly. As an alternative to this approach, our statistical model is only based on the additivity assumption; the proposed method does not regress observations onto expected response patterns. We introduce estimation and testing procedures based on likelihood maximization, and show that climate modelling uncertainty can easily be accounted for. Some discussion is provided on how to practically estimate the climate modelling uncertainty based on an ensemble of opportunity. Our approach is based on the “models are statistically indistinguishable from the truth” paradigm, where the difference between any given model and the truth has the same distribution as the difference between any pair of models, but other choices might also be considered. The properties of this approach are illustrated and discussed based on synthetic data. Lastly, the method is applied to the linear trend in global mean temperature over the period 1951–2010. Consistent with the last IPCC assessment report, we find that most of the observed warming over this period (+0.65 K) is attributable to anthropogenic forcings (+0.67 $$\pm$$ 0.12 K, 90 % confidence range), with a very limited contribution from natural forcings ( $$-0.01\pm 0.02$$ K).

Radiative analysis of global mean temperature trends in the middle atmosphere: Effects of non-locality and secondary absorption bands

In this paper, we provide a refined and extended assignment of past and future temperature changes relative to previous analyses and describe and evaluate the relevance of vertical coupling and non-linear and secondary radiative mechanisms for the interpretation of climatic temperature variations in the middle atmosphere. Because of their nature, the latter mechanisms are not adequately accounted for in most regression analyses of temperature trends as a function of local constituent variations. These mechanisms are examined using (1) globally averaged profiles from transient simulations with the Canadian Middle Atmosphere Model (CMAM) forced by changes in greenhouse gases and ozone depleting substances and (2) a one-dimensional radiative-equilibrium model forced using the diagnosed global mean changes in radiatively active constituents as derived from the CMAM model runs. The conditions during the periods 1975 to 1995 and 2010 to 2040 (during which the rates of change in ozone and CO2 differ) provide a suitable contrast for the role of the non-linear and non-local mechanisms being evaluated in this paper to be clearly differentiated and evaluated. Vertical coupling of radiative transfer effects and the influence of secondary absorption bands are important enough to render the results of multiple linear regression analyses between the temperature response and constituent changes misleading. These effects are evaluated in detail using the 1D radiative-equilibrium model using profiles from the CMAM runs as inputs. In order to explain the differences in the CMAM temperature trends prior to and after 2000 these other radiative effects must be considered in addition to local changes in the radiatively active species. The middle atmosphere temperature cools in response to CO2 and water vapor increases, but past and future trends are modulated by ozone changes.

The Origin and Development of the Central European Man-made Landscape, Habitat and Species Diversity as Affected by Climate and its Changes – a Review

The Origin and Development of the Central European Man-made Landscape, Habitat and Species Diversity as Affected by Climate and its Changes – a Review

Competition between global warming and an abrupt collapse of the AMOC in Earth's energy imbalance.

A collapse of the Atlantic Meridional Overturning Circulation (AMOC) leads to global cooling through fast feedbacks that selectively amplify the response in the Northern Hemisphere (NH). How such cooling competes with global warming has long been a topic for speculation, but was never addressed using a climate model. Here it is shown that global cooling due to a collapsing AMOC obliterates global warming for a period of 15–20 years. Thereafter, the global mean temperature trend is reversed and becomes similar to a simulation without an AMOC collapse. The resulting surface warming hiatus lasts for 40–50 years. Global warming and AMOC-induced NH cooling are governed by similar feedbacks, giving rise to a global net radiative imbalance of similar sign, although the former is associated with surface warming, the latter with cooling. Their footprints in outgoing longwave and absorbed shortwave radiation are very distinct, making attribution possible.

AMSU-A-Only Atmospheric Temperature Data Records from the Lower Troposphere to the Top of the Stratosphere

Abstract The Advanced Microwave Sounding Unit-A (AMSU-A, 1998–present) not only continues but surpasses the Microwave Sounding Unit’s (MSU, 1978–2006) capability in atmospheric temperature observation. It provides valuable satellite measurements for higher vertical resolution and long-term climate change research and trend monitoring. This study presented methodologies for generating 11 channels of AMSU-A-only atmospheric temperature data records from the lower troposphere to the top of the stratosphere. The recalibrated AMSU-A level 1c radiances recently developed by the Center for Satellite Applications and Research group were used. The recalibrated radiances were adjusted to a consistent sensor incidence angle (nadir), channel frequencies (prelaunch-specified central frequencies), and observation time (local solar noon time). Radiative transfer simulations were used to correct the sensor incidence angle effect and the National Oceanic and Atmospheric Administration-15 (NOAA-15) channel 6 frequency shift. Multiyear averaged diurnal/semidiurnal anomaly climatologies from climate reanalysis as well as climate model simulations were used to adjust satellite observations to local solar noon time. Adjusted AMSU-A measurements from six satellites were carefully quality controlled and merged to generate 13+ years (1998–2011) of a monthly 2.5° × 2.5° gridded atmospheric temperature data record. Major trend features in the AMSU-A-only atmospheric temperature time series, including global mean temperature trends and spatial trend patterns, were summarized.

The impact of volcanic eruptions in the period 2000–2013 on global mean temperature trends evaluated in the HadGEM2‐ES climate model

AbstractThe slow‐down in global warming over the last decade has lead to significant debate about whether the causes are of natural or anthropogenic origin. Using an ensemble of HadGEM2‐ES coupled climate model simulations we investigate the impact of overlooked modest volcanic eruptions. We deduce a global mean cooling of around −0.02 to −0.03 K over the period 2008–2012. Thus while these eruptions do cause a cooling of the Earth and may therefore contribute to the slow‐down in global warming, they do not appear to be the sole or primary cause.