Mean Surface Temperature Anomalies Research Articles

Explaining Forcing Efficacy With Pattern Effect and State Dependence

AbstractThe magnitude of global surface temperature change in response to unit radiative forcing depends on the type and magnitude of forcing agent—a concept known as a “forcing efficacy.” However, the mechanisms behind the forcing efficacy are still unclear. In this study, we perform a set of simulations using CESM1 to calculate the efficacy of 10 different forcing agents defined in terms of fixed‐SST effective radiative forcing, and then use a Green's function approach to show that each forcing efficacy can be largely understood in terms of the radiative feedbacks associated with the different surface temperature patterns induced by the forcing agents (a pattern effect). We also quantify how the state dependence of feedbacks on global mean surface temperature anomalies impacts forcing efficacies. The results show that the forcing efficacy can be well reconstructed with a combination of pattern effect and state dependence.

An Assessment of the Impact of Temperature Rise Due to Climate Change on Asphalt Pavement in China

In the global warming context, understanding the impact of temperature rise on asphalt pavement is the basis for making adaptation strategies. An approach based on historical climate data and pavement performance models was employed to assess the potential impact of temperature rise on asphalt pavement in China. It is shown that permanent deformation is one sensitive aspect of asphalt pavement performance, which increased on average by 20.70% from 1992 to 2019. Another one is low-temperature cracking, which decreased by 20.99% from 1970 to 1997, but has remained almost unchanged since 1997. Global mean surface temperature anomalies of 1.5 °C and 2.0 °C will increase the permanent deformation of asphalt pavement by 18.63% and 36.71%, respectively, compared to 2019. Global warming is bringing serious challenges to the structure and material design of asphalt pavement due to the increasing service temperature range.

Global climate disruption and regional climate shelters after the Toba supereruption

The Toba eruption ∼74,000 y ago was the largest volcanic eruption since the start of the Pleistocene and represents an important test case for understanding the effects of large explosive eruptions on climate and ecosystems. However, the magnitude and repercussions of climatic changes driven by the eruption are strongly debated. High-resolution paleoclimate and archaeological records from Africa find little evidence for the disruption of climate or human activity in the wake of the eruption in contrast with a controversial link with a bottleneck in human evolution and climate model simulations predicting strong volcanic cooling for up to a decade after a Toba-scale eruption. Here, we use a large ensemble of high-resolution Community Earth System Model (CESM1.3) simulations to reconcile climate model predictions with paleoclimate records, accounting for uncertainties in the magnitude of Toba sulfur emissions with high and low emission scenarios. We find a near-zero probability of annual mean surface temperature anomalies exceeding 4 °C in most of Africa in contrast with near 100% probabilities of cooling this severe in Asia and North America for the high sulfur emission case. The likelihood of strong decreases in precipitation is low in most of Africa. Therefore, even Toba sulfur release at the upper range of plausible estimates remains consistent with the muted response in Africa indicated by paleoclimate proxies. Our results provide a probabilistic view of the uneven patterns of volcanic climate disruption during a crucial interval in human evolution, with implications for understanding the range of environmental impacts from past and future supereruptions.

Long-term trends in Arctic surface temperature and potential causality over the last 100 years

The rate of warming of the Arctic surface temperature has exceeded that of the global surface temperature in recent decades. However, the underlying process and causes of the long-term warming remain uncertain. In this paper, we explored the factors underlying variation in Arctic mean surface temperature anomalies (AMTA) using a piecewise linear model for 1920–2018. This analysis indicated that the change in AMTA during the study period could be divided into three segments, with AMTA increasing from 1920 to 1938, declining from 1939 to 1976, and finally increasing rapidly after 1977. By a newly developed rigorous formalism of information flow, we found a one-way causality from the driving forces to AMTA. Moreover, the AMTA evolution could mainly be attributed to a combined effect of anthropogenic and natural factors (e.g., CO2, aerosol, and PDO). During the first warming stage (1920–1938), the PDO and aerosols are the main factors determining the change in AMTA. During the second warming stage (1977–2018), greenhouse gases, dominated by CO2, are the major factors accounting for the Arctic warming. In 1939–1976, the observed cooling may be associated with aerosols, clouds, and land use. A better understanding of the driving mechanism underlying AMTA evolution provides insight into the historical Arctic climate change, and can improve the prediction of future changes in AMTA.

Decadal Attribution of Historic Temperature and Ocean Heat Content Change to Anthropogenic Emissions

AbstractWe present an alternative method of calculating the historical effective radiative forcing using the observed temperature record and a kernel based on the 5th Climate Model Intercomparison Project (CMIP5) temperature response. This estimate is the effective radiative forcing time series that the average climate model would need to simulate the observed global mean surface temperature anomalies. We further infer the anthropogenic aerosols radiative forcing as a residual using the better‐known greenhouse gas radiative forcing. This allows an independent estimate of anthropogenic aerosol radiative forcing, which suggests a cooling influence due to aerosols in the early part of the twentieth century. The temporal kernels are also used to calculate decadal contributions from the dominant forcing agents to present‐day temperature, ocean heat content, and thermosteric sea level rise. The current global mean temperature anomaly is dominated by emissions in the past two decades, while current ocean heat content is more strongly affected by earlier decades.

Estimates of climate system properties incorporating recent climate change

Abstract. Historical time series of surface temperature and ocean heat content changes are commonly used metrics to diagnose climate change and estimate properties of the climate system. We show that recent trends, namely the slowing of surface temperature rise at the beginning of the 21st century and the acceleration of heat stored in the deep ocean, have a substantial impact on these estimates. Using the Massachusetts Institute of Technology Earth System Model (MESM), we vary three model parameters that influence the behavior of the climate system: effective climate sensitivity (ECS), the effective ocean diffusivity of heat anomalies by all mixing processes (Kv), and the net anthropogenic aerosol forcing scaling factor. Each model run is compared to observed changes in decadal mean surface temperature anomalies and the trend in global mean ocean heat content change to derive a joint probability distribution function for the model parameters. Marginal distributions for individual parameters are found by integrating over the other two parameters. To investigate how the inclusion of recent temperature changes affects our estimates, we systematically include additional data by choosing periods that end in 1990, 2000, and 2010. We find that estimates of ECS increase in response to rising global surface temperatures when data beyond 1990 are included, but due to the slowdown of surface temperature rise in the early 21st century, estimates when using data up to 2000 are greater than when data up to 2010 are used. We also show that estimates of Kv increase in response to the acceleration of heat stored in the ocean as data beyond 1990 are included. Further, we highlight how including spatial patterns of surface temperature change modifies the estimates. We show that including latitudinal structure in the climate change signal impacts properties with spatial dependence, namely the aerosol forcing pattern, more than properties defined for the global mean, climate sensitivity, and ocean diffusivity.

Comparison of Intraseasonal East Asian Winter Cold Temperature Anomalies in Positive and Negative Phases of the Arctic Oscillation

AbstractThis study investigates the relationship between intraseasonal variations of the Arctic Oscillation (AO) and East Asian winter temperature. Based on the lead‐lag correlation between 30‐ and 60‐day band‐pass filtered daily AO index and regional mean surface temperature anomalies over eastern China, it is found that the cold temperature anomalies occur following both positive and negative AO phases with nearly the same probability. Composite analysis reveals prominent differences in surface temperature and tropospheric circulation anomalies between the two types of years. During the years when negative AO leads cold anomalies over East Asia, the AO‐related pressure anomalies extend to Eurasia, inducing an enhanced Siberian high with a large spatial coverage in midlatitude and high latitude; the midtropospheric wave train along the polar front jet takes an eastward path and induces the deepening of the East Asian trough; the resultant cold surface temperature anomalies affect a large region over East Asia. During the years when positive AO leads cold anomalies, the AO‐related pressure anomalies extend to North America and the high pressure anomalies over East Asia are located at midlatitudes with a relatively small spatial coverage; the midtropospheric wave train along the polar front jet takes a southward path over Asia, inducing the development of a trough over subtropical Asia with a supplementary contribution from a subtropical wave train; the resultant cold surface temperature anomalies influence inland East Asia with a relatively small extent. There appears to be a notable difference in the relationship between the stratospheric and tropospheric change between the two types of years.

Can an ensemble climate simulation be used to separate climate change signals from internal unforced variability?

The contribution of internal unforced variability to climate change is explored using a 100-member ensemble climate simulation for the period 1850–2005. The ensemble simulation is based on the Max Planck Institute for Meteorology climate model, ECHAM6, where all members have been exposed to the identically same radiative forcing. The range of global mean surface temperature warming over the 1850–2005 period, based on all members, is 0.65–1.10 °C. The distribution of the global mean surface temperature about the ensemble mean has a standard deviation (StD) of ~ 0.14 °C which slowly decreases in time. Regionally, the largest decrease in the ensemble StD occurs in the Northern Hemisphere winter. Comparing the temporal StD with that from the observed HadCRUT4 surface temperature data indicates that the majority of the ensemble members have a larger temporal StD than the observations suggesting that the model simulations might overestimate the variance. There are clear random 20-year linear trends in global mean surface temperature anomalies as well as significant regional 50-year linear trends. Even with an ensemble mean warming trend, typical of the early twenty-first century, a global hiatus in temperature of 20 years duration is possible to occur by chance. The results support the view that observed decadal and multi-decadal anomalies in the twentieth century were significantly influenced by internal processes of the climate system. This is particularly the case for the observed global warming trend of 1910–1940 and the global cooling trend of 1940–1970. Global mean precipitation hardly increases with time in the ensemble simulations, but in agreement with theory regional changes occur, with increasing precipitation in polar regions and in some tropical areas. In the subtropics there are reductions in precipitation. Long-lasting regional anomalies of significant amplitudes occur by chance in the ensemble integration.

The relation between natural variations in ocean heat uptake and global mean surface temperature anomalies in CMIP5

It is still unclear whether a hiatus period arises due to a vertical redistribution of ocean heat content (OHC) without changing ocean heat uptake (OHU), or whether the increasing radiative forcing is associated with an increase in OHU when global mean surface temperature (GMST) rise stalls. By isolating natural variability from forced trends and performing a more precise lead-lag analysis, we show that in climate models TOA radiation and OHU do anti-correlate with natural variations in GMST, when GMST leads or when they coincide, but the correlation changes sign when OHU leads. Surface latent and sensible heat fluxes always force GMST-variations, whilst net surface longwave and solar radiation fluxes have a damping effect, implying that natural GMST-variations are caused by oceanic heat redistribution. In the models an important trigger for a hiatus period on decadal timescales is increased reflection of solar radiation, by increased sea-ice cover over deep-water formation areas. On inter-annual timescales, reflection of solar radiation in the tropics by increased cloud cover associated with La Niña is most important and the subsequent reduction in latent heat release becomes the dominant cause for a hiatus.

Multiscale combination of climate model simulations and proxy records over the last millennium

To highlight the compatibility of climate model simulation and proxy reconstruction at different timescales, a timescale separation merging method combining proxy records and climate model simulations is presented. Annual mean surface temperature anomalies for the last millennium (851–2005 AD) at various scales over the land of the Northern Hemisphere were reconstructed with 2° × 2° spatial resolution, using an optimal interpolation (OI) algorithm. All target series were decomposed using an ensemble empirical mode decomposition method followed by power spectral analysis. Four typical components were obtained at inter-annual, decadal, multidecadal, and centennial timescales. A total of 323 temperature-sensitive proxy chronologies were incorporated after screening for each component. By scaling the proxy components using variance matching and applying a localized OI algorithm to all four components point by point, we obtained merged surface temperatures. Independent validation indicates that the most significant improvement was for components at the inter-annual scale, but this became less evident with increasing timescales. In mid-latitude land areas, 10–30% of grids were significantly corrected at the inter-annual scale. By assimilating the proxy records, the merged results reduced the gap in response to volcanic forcing between a pure reconstruction and simulation. Difficulty remained in verifying the centennial information and quantifying corresponding uncertainties, so additional effort should be devoted to this aspect in future research.

On the causal structure between CO2 and global temperature

We use a newly developed technique that is based on the information flow concept to investigate the causal structure between the global radiative forcing and the annual global mean surface temperature anomalies (GMTA) since 1850. Our study unambiguously shows one-way causality between the total Greenhouse Gases and GMTA. Specifically, it is confirmed that the former, especially CO2, are the main causal drivers of the recent warming. A significant but smaller information flow comes from aerosol direct and indirect forcing, and on short time periods, volcanic forcings. In contrast the causality contribution from natural forcings (solar irradiance and volcanic forcing) to the long term trend is not significant. The spatial explicit analysis reveals that the anthropogenic forcing fingerprint is significantly regionally varying in both hemispheres. On paleoclimate time scales, however, the cause-effect direction is reversed: temperature changes cause subsequent CO2/CH4 changes.

Scale-dependency of the global mean surface temperature trend and its implication for the recent hiatus of global warming.

Studies of the global mean surface temperature trend are typically conducted at a single (usually annual or decadal) time scale. The used scale does not necessarily correspond to the intrinsic scales of the natural temperature variability. This scale mismatch complicates the separation of externally forced temperature trends from natural temperature fluctuations. The hiatus of global warming since 1999 has been claimed to show that human activities play only a minor role in global warming. Most likely this claim is wrong due to the inadequate consideration of the scale-dependency in the global surface temperature (GST) evolution. Here we show that the variability and trend of the global mean surface temperature anomalies (GSTA) from January 1850 to December 2013, which incorporate both land and sea surface data, is scale-dependent and that the recent hiatus of global warming is mainly related to natural long-term oscillations. These results provide a possible explanation of the recent hiatus of global warming and suggest that the hiatus is only temporary.

Reconciling warming trends

Any divergence between real-world climate phenomena and prior expectations poses interesting science questions. The case of the apparent slow-down of warming since the record El Nino event in 1997/1998 is no exception. The global mean surface temperature trend was smaller 1 between 1997 and 2013 (0.07±0.08 °C per decade) than over the last 50 years (0.16 ± 0.02 °C per decade), highlighting questions about the mechanisms that regulate decadal variability in the Earth’s temperature. In addition, the warming trend in the most recent 15-year period is near the lower edge of the 5–95% range of projections from a collection of climate models that were part of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Why most of the model simulations suggest more warming than has been observed is a second question that deserves further exploration. Short-term fluctuations in global mean surface temperature anomalies have been a perennial focus of public discussions related to climate change. We should expect to see climate changes, by definition, only in the long-term trends that average over stochastic weather and year-to-year fluctuations such as those associated with the El Nino/Southern Oscillation (ENSO), which favoured a cool La Nina phase in the past few years. On decadal timescales, global mean surface temperatures are expected to vary, too. One cause might be the chaotic internal variability of the coupled system of oceans and atmosphere, for example in the tropical Pacific Ocean 2

Estimation of impulse response of Earth's climate system at short time intervals

A method is described for restoration of the impulse response h(t) of the Earth's climate system (ECS), which is regarded as a time-invariant linear dynamic system whose input is the change in solar constant, and output—the global mean surface temperature anomalies. Search for solution of the ill-posed inverse problem is carried out on a compact set of non-negative, monotonically non-increasing, convex downward functions. This suggests that ECS may be a first-order dynamic system or a set of similar independent subsystems with different time constants. Results of restoration of h(t) at time intervals up to 100 months show that it is a rapidly decreasing function, which does not differ from zero for t>3 months. An estimate of the equivalent time constant gives the average value of 1.04±0.17 months. The sensitivity of the ECS to changes in radiative forcing at the top of the atmosphere is equal to 0.41±0.05KW−1m2.

The observed sensitivity of high clouds to mean surface temperature anomalies in the tropics

[1] Cloud feedback represents the source of largest diversity in projections of future warming. Observational constraints on both the sign and magnitude of the feedback are limited, since it is unclear how the natural variability that can be observed is related to secular climate change, and analyses have rarely been focused on testable physical theories for how clouds should respond to climate change. In this study we use observations from a suite of satellite instruments to assess the sensitivity of tropical high clouds to interannual tropical mean surface temperature anomalies. We relate cloud changes to a physical governing mechanism that is sensitive to the vertical structure of warming. Specifically, we demonstrate that the mean and interannual variability in both the altitude and fractional coverage of tropical high clouds as measured by CloudSat, the Moderate Resolution Imaging Spectroradiometer, the Atmospheric Infrared Sounder, and the International Satellite Cloud Climatology Project are well diagnosed by upper tropospheric convergence computed from the mass and energy budget of the clear-sky atmosphere. Observed high clouds rise approximately isothermally in accordance with theory and exhibit an overall reduction in coverage when the tropics warms, similar to their behavior in global warming simulations. Such cloud changes cause absorbed solar radiation to increase more than does outgoing longwave radiation, resulting in a positive but statistically insignificant net high cloud feedback in response to El Nino–Southern Oscillation. The results suggest that the convergence metric based on simple mass and energy budget constraints may be a powerful tool for understanding observed and modeled high cloud behavior and for evaluating the realism of modeled high cloud changes in response to a variety of forcings.

The role of natural climatic variation in perturbing the observed global mean temperature trend

Controversy continues to prevail concerning the reality of anthropogenically-induced climatic warming. One of the principal issues is the cause of the hiatus in the current global warming trend. There appears to be a widely held view that climatic change warming should exhibit an inexorable upwards trend, a view that implies there is no longer any input by climatic variability in the existing climatic system. The relative roles of climatic change and climatic variability are examined here using the same coupled global climatic model. For the former, the model is run using a specified CO2 growth scenario, while the latter consisted of a multi-millennial simulation where any climatic variability was attributable solely to internal processes within the climatic system. It is shown that internal climatic variability can produce global mean surface temperature anomalies of ±0.25 K and sustained positive and negative anomalies sufficient to account for the anomalous warming of the 1940s as well as the present hiatus in the observed global warming. The characteristics of the internally-induced negative temperature anomalies are such that if this internal natural variability is the cause of the observed hiatus, then a resumption of the observed global warming trend is to be expected within the next few years.

Hemispheric asymmetry of surface temperature anomalies

In recent months there has been some controversy concerning the possible effect of suspended sulfate aerosols on warming trends predicted to occur in response to steadily increasing greenhouse gas concentrations in the troposphere. Evidence in the recent literature both supporting and doubting the theory that aerosols have suppressed warming in the Northern Hemisphere more than in the Southern Hemisphere has relied on analyses of radiosonde observations covering various periods between 1958 and 1995. In this letter the UK Met Office/University of East Anglia Climatic Research Unit (Parker/Jones) data sets of mean surface temperature anomalies over land and sea for the past 140 years serve as an independent data base to test earlier reported results obtained from radiosonde observations. The results suggest that there is no evidence of any systematic differences in temperature trends between the two hemispheres.

Satellite versus Surface Estimates of Air Temperature since 1979

Abstract A comparison of near-global monthly mean surface temperature anomalies to those of global Microwave Sounding Unit (MSU) 2R temperatures for 1979–95 reveals differences in global annual mean trends that are shown to be largely attributable to important physical differences in the quantities that are measured. Maps of standard deviations of the monthly mean anomalies, which can be viewed as mostly measuring the size of the climate signal, reveal pronounced differences regionally in each dataset. At the surface, the variability of temperatures is relatively small over the oceans but large over land, whereas in the MSU record the signal is much more zonally symmetric. The largest differences are found over the North Pacific and North Atlantic Oceans where the monthly standard deviations of the MSU temperatures are larger by more than a factor of 2. Locally over land, the variance of the surface record is larger than that of the MSU. In addition to differential responses to forcings from the El Nino-S...

Monthly and seasonal numerical forecasts by using the anomaly ocean-atmosphere coupled filtered model

Case experiments of monthly predictions of eight winter months during 1976–1977 and 1982–1983 El Nino events are performed by using a three-layer anomalous filtered model (AFM), in which transient Rossby waves are filtered. The results show that this model predicts successfully the large-scale patterns of the monthly mean surface temperature anomalies. The correlation coefficients between observations and predictions are basically higher than those of persistence predictions. By comparison with the anomalous general circulation model (AGCM) the AFM gives almost the identical results, but the computation time required for running the AFM is nearly 100 times less than that required for running the AGCM. It is also shown that the results of the three-layer model are better than those of the one-layer model. In the meanwhile, four seasonal forecasts are also carried out by using the same model. It seems that the AFM possesses potential ability in predicting large-scale circulation anomalies.

Specification of monthly mean surface temperature anomalies in Europe and Asia from concurrent 700 mb monthly mean height anomalies over the Northern Hemisphere

AbstractSpecification equations for the monthly mean air temperature anomalies at 115 surface stations in Eurasia are derived by applying a stepwise forward screening procedure to the simultaneous monthly mean 700 mb height anomalies at 134 grid points in the northern hemisphere and the previous month's local temperature. These equations explain about 65 per cent of the temperature variance by an average of only 4.7 variables, but with marked regional, seasonal and month‐to‐month variations. The main properties of the equations are highlighted by means of several maps and graphs that delineate important spatial and temporal variations.The average properties of the specification equations in the European sector closely resemble those derived previously for North America. However, the results are consistently poorer for stations in Asia, not only for the annual mean, but also during each of the four seasons. Furthermore, the phases of seasonal variation are opposite in Europe and Asia. In both sectors, however, the equations are better in winter than in summer at coastal stations, but the reverse is true at continental stations. The average error in specifying monthly average surface temperature from perfect 700 mb height forecasts should be less than 0.9°C in Europe and 1.2°C in Asia about two‐thirds of the time.