Associations between elevated atmospheric temperature and human mortality: a critical review of the literature

The effects of the anomalously warm European summer of 2003 highlighted the importance of understanding the relationship between elevated atmospheric temperature and human mortality. This review is an extension of the brief evidence examining this relationship provided in the IPCC’s Assessment Reports. A comprehensive and critical review of the literature is presented, which highlights avenues for further research, and the respective merits and limitations of the methods used to analyse the relationships. In contrast to previous reviews that concentrate on the epidemiological evidence, this review acknowledges the inter-disciplinary nature of the topic and examines the evidence presented in epidemiological, environmental health, and climatological journals. As such, present temperature–mortality relationships are reviewed, followed by a discussion of how these are likely to change under climate change scenarios. The importance of uncertainty, and methods to include it in future work, are also considered.

Identifying human influences on atmospheric temperature

We perform a multimodel detection and attribution study with climate model simulation output and satellite-based measurements of tropospheric and stratospheric temperature change. We use simulation output from 20 climate models participating in phase 5 of the Coupled Model Intercomparison Project. This multimodel archive provides estimates of the signal pattern in response to combined anthropogenic and natural external forcing (the finger-print) and the noise of internally generated variability. Using these estimates, we calculate signal-to-noise (S/N) ratios to quantify the strength of the fingerprint in the observations relative to fingerprint strength in natural climate noise. For changes in lower stratospheric temperature between 1979 and 2011, S/N ratios vary from 26 to 36, depending on the choice of observational dataset. In the lower troposphere, the fingerprint strength in observations is smaller, but S/N ratios are still significant at the 1% level or better, and range from three to eight. We find no evidence that these ratios are spuriously inflated by model variability errors. After removing all global mean signals, model fingerprints remain identifiable in 70% of the tests involving tropospheric temperature changes. Despite such agreement in the large-scale features of model and observed geographical patterns of atmospheric temperature change, most models do not replicate the size of the observed changes. On average, the models analyzed underestimate the observed cooling of the lower stratosphere and overestimate the warming of the troposphere. Although the precise causes of such differences are unclear, model biases in lower stratospheric temperature trends are likely to be reduced by more realistic treatment of stratospheric ozone depletion and volcanic aerosol forcing.

Tropospheric temperature trends: history of an ongoing controversy

Changes in atmospheric temperature have a particular importance in climate research because climate models consistently predict a distinctive vertical profile of trends. With increasing greenhouse gas concentrations, the surface and troposphere are consistently projected to warm, with an enhancement of that warming in the tropical upper troposphere. Hence, attempts to detect this distinct ‘fingerprint’ have been a focus for observational studies. The topic acquired heightened importance following the 1990 publication of an analysis of satellite data which challenged the reality of the projected tropospheric warming. This review documents the evolution over the last four decades of understanding of tropospheric temperature trends and their likely causes. Particular focus is given to the difficulty of producing homogenized datasets, with which to derive trends, from both radiosonde and satellite observing systems, because of the many systematic changes over time. The value of multiple independent analyses is demonstrated. Paralleling developments in observational datasets, increased computer power and improved understanding of climate forcing mechanisms have led to refined estimates of temperature trends from a wide range of climate models and a better understanding of internal variability. It is concluded that there is no reasonable evidence of a fundamental disagreement between tropospheric temperature trends from models and observations when uncertainties in both are treated comprehensively

An observing system simulation experiment for climate monitoring with GNSS radio occulation data: setup and testbed study

The long-term stability, high accuracy, all-weather capability, high vertical resolution, and global coverage of Global Navigation Satellite System (GNSS) radio occultation (RO) suggests it as a promising tool for global monitoring of atmospheric temperature change. With the aim to investigate and quantify how well a GNSS RO observing system is able to detect climate trends, we are currently performing an (climate) observing system simulation experiment over the 25-year period 2001 to 2025, which involves quasi-realistic modeling of the neutral atmosphere and the ionosphere. We carried out two climate simulations with the general circulation model MAECHAM5 (Middle Atmosphere European Centre/Hamburg Model Version 5) of the MPI-M Hamburg, covering the period 2001–2025: One control run with natural variability only and one run also including anthropogenic forcings due to greenhouse gases, sulfate aerosols, and tropospheric ozone. On the basis of this, we perform quasi-realistic simulations of RO observables for a small GNSS receiver constellation (six satellites), state-of-the-art data processing for atmospheric profiles retrieval, and a statistical analysis of temperature trends in both the “observed” climatology and the “true” climatology. Here we describe the setup of the experiment and results from a test bed study conducted to obtain a basic set of realistic estimates of observational errors (instrument- and retrieval processing-related errors) and sampling errors (due to spatial-temporal undersampling). The test bed results, obtained for a typical summer season and compared to the climatic 2001–2025 trends from the MAECHAM5 simulation including anthropogenic forcing, were found encouraging for performing the full 25-year experiment. They indicated that observational and sampling errors (both contributing about 0.2 K) are consistent with recent estimates of these errors from real RO data and that they should be sufficiently small for monitoring expected temperature trends in the global atmosphere over the next 10 to 20 years in most regions of the upper troposphere and lower stratosphere (UTLS). Inspection of the MAECHAM5 trends in different RO-accessible atmospheric parameters (microwave refractivity and pressure/geopotential height in addition to temperature) indicates complementary climate change sensitivity in different regions of the UTLS so that optimized climate monitoring shall combine information from all climatic key variables retrievable from GNSS RO data.

Statistical downscaling of river flows

An extensive statistical ‘downscaling’ study is done to relate large-scale climate information from a general circulation model (GCM) to local-scale river flows in SW France for 51 gauging stations ranging from nival (snow-dominated) to pluvial (rainfall-dominated) river-systems. This study helps to select the appropriate statistical method at a given spatial and temporal scale to downscale hydrology for future climate change impact assessment of hydrological resources. The four proposed statistical downscaling models use large-scale predictors (derived from climate model outputs or reanalysis data) that characterize precipitation and evaporation processes in the hydrological cycle to estimate summary flow statistics. The four statistical models used are generalized linear (GLM) and additive (GAM) models, aggregated boosted trees (ABT) and multi-layer perceptron neural networks (ANN). These four models were each applied at two different spatial scales, namely at that of a single flow-gauging station (local downscaling) and that of a group of flow-gauging stations having the same hydrological behaviour (regional downscaling). For each statistical model and each spatial resolution, three temporal resolutions were considered, namely the daily mean flows, the summary statistics of fortnightly flows and a daily ‘integrated approach’. The results show that flow sensitivity to atmospheric factors is significantly different between nival and pluvial hydrological systems which are mainly influenced, respectively, by shortwave solar radiations and atmospheric temperature. The non-linear models (i.e. GAM, ABT and ANN) performed better than the linear GLM when simulating fortnightly flow percentiles. The aggregated boosted trees method showed higher and less variable R2 values to downscale the hydrological variability in both nival and pluvial regimes. Based on GCM cnrm-cm3 and scenarios A2 and A1B, future relative changes of fortnightly median flows were projected based on the regional downscaling approach. The results suggest a global decrease of flow in both pluvial and nival regimes, especially in spring, summer and autumn, whatever the considered scenario. The discussion considers the performance of each statistical method for downscaling flow at different spatial and temporal scales as well as the relationship between atmospheric processes and flow variability.

Radiative forcing and global warming potentials of 11 halogenated compounds

Radiative forcing values have been calculated for 11 halogenated compounds which are in current use or which have been suggested as possible replacements for the chlorofluorocarbons. Absorption cross-sections measured over a range of atmospheric temperature and pressure conditions as part of a multi-laboratory programme have been used together with a narrow band radiative transfer model. We provide a “best estimate” radiative forcing taking into account the likely vertical profile of the gas in each case. The Global Warming Potential over a variety of time horizons has also been calculated where the lifetime is available. We present the first such information for 1,2-dichloroethane. For chloroform our radiative forcing is 5 times higher than the value used in previous assessments, possibly because these ignored the effect of absorption outside the 800–1200 cm−1 “window”. For several of the other compounds considered here, our forcing is between 10 and 30% lower than previous assessments. The perfluorocarbons have been found to have large global warming potentials, many times that of CFC-11, due to both strong absorption and long lifetimes. The importance of absorption features at wavenumbers below 800 cm−1 and the effect of temperature variations in absorption cross-section on the radiative forcing are also investigated.

Ice-stream initiation, duration and thinning on James Ross Island, northern Antarctic Peninsula

Predicting the future response of the Antarctic Ice Sheet to climate change requires an understanding of the ice streams that dominate its dynamics. Here we use cosmogenic isotope exposure-age dating (26Al, 10Be and 36Cl) of erratic boulders on ice-free land on James Ross Island, north-eastern Antarctic Peninsula, to define the evolution of Last Glacial Maximum (LGM) ice in the adjacent Prince Gustav Channel. These data include ice-sheet extent, thickness and dynamical behaviour. Prior to ∼18 ka, the LGM Antarctic Peninsula Ice Sheet extended to the continental shelf-edge and transported erratic boulders onto high-elevation mesas on James Ross Island. After ∼18 ka there was a period of rapid ice-sheet surface-lowering, coincident with the initiation of the Prince Gustav Ice Stream. This timing coincided with rapid increases in atmospheric temperature and eustatic sea-level rise around the Antarctic Peninsula. Collectively, these data provide evidence for a transition from a thick, cold-based LGM Antarctic Peninsula Ice Sheet to a thinner, partially warm-based ice sheet during deglaciation.

Sea level extremes at the coasts of China

Hourly sea level records from 1954 to 2012 at 20 tide gauges at and adjacent to the Chinese coasts are used to analyze extremes in sea level and in tidal residual. Tides and tropical cyclones determine the spatial distribution of sea level maxima. Tidal residual maxima are predominantly determined by tropical cyclones. The 50 year return level is found to be sensitive to the number of extreme events used in the estimation. This is caused by the small number of tropical cyclone events happening each year which lead to other local storm events included thus significantly affecting the estimates. Significant increase in sea level extremes is found with trends in the range between 2.0 and 14.1 mm yr−1. The trends are primarily driven by changes in median sea level but also linked with increases in tidal amplitudes at three stations. Tropical cyclones cause significant interannual variations in the extremes. The interannual variability in the sea level extremes is also influenced by the changes in median sea level at the north and by the 18.6 year nodal cycle at the South China Sea. Neither of PDO and ENSO is found to be an indicator of changes in the size of extremes, but ENSO appears to regulate the number of tropical cyclones that reach the Chinese coasts. Global mean atmospheric temperature appears to be a good descriptor of the interannual variability of tidal residual extremes induced by tropical cyclones but the trend in global temperature is inconsistent with the lack of trend in the residuals.

A coupled cloud physics–radiation parameterization of the bulk optical properties of cirrus and its impact on the Met Office unified model global atmosphere 5.0 configuration

A new coupled cloud physics–radiation parameterization of the bulk optical properties of ice clouds is presented. The parameterization is consistent with assumptions in the cloud physics scheme regarding particle size distributions (PSDs) and mass–dimensional relationships. The parameterization is based on a weighted ice crystal habit mixture model, and its bulk optical properties are parameterized as simple functions of wavelength and ice water content (IWC). This approach directly couples IWC to the bulk optical properties, negating the need for diagnosed variables, such as the ice crystal effective dimension. The parameterization is implemented into the Met Office Unified Model Global Atmosphere 5.0 (GA5) configuration. The GA5 configuration is used to simulate the annual 20-yr shortwave (SW) and longwave (LW) fluxes at the top of the atmosphere (TOA), as well as the temperature structure of the atmosphere, under various microphysical assumptions. The coupled parameterization is directly compared against the current operational radiation parameterization, while maintaining the same cloud physics assumptions. In this experiment, the impacts of the two parameterizations on the SW and LW radiative effects at TOA are also investigated and compared against observations. The 20-yr simulations are compared against the latest observations of the atmospheric temperature and radiative fluxes at TOA. The comparisons demonstrate that the choice of PSD and the assumed ice crystal shape distribution are as important as each other. Moreover, the consistent radiation parameterization removes a long-standing tropical troposphere cold temperature bias but slightly warms the southern midlatitudes by about 0.5 K.

Origin and impact of initialisation shocks in coupled atmosphere-ocean forecasts

Current methods for initialising coupled atmosphere-ocean forecasts often rely on the use of separate atmosphere and ocean analyses, the combination of which can leave the coupled system imbalanced at the beginning of the forecast, potentially accelerating the development of errors. Using a series of experiments with the European Centre for Medium-range Weather Forecasts coupled system, the magnitude and extent of these so-called initialisation shocks is quantified, and their impact on forecast skill measured. It is found that forecasts initialised by separate ocean and atmospheric analyses do exhibit initialisation shocks in lower atmospheric temperature, when compared to forecasts initialised using a coupled data assimilation method. These shocks result in as much as a doubling of root-mean-square error on the first day of the forecast in some regions, and in increases that are sustained for the duration of the 10-day forecasts performed here. However, the impacts of this choice of initialisation on forecast skill, assessed using independent datasets, were found to be negligible, at least over the limited period studied. Larger initialisation shocks are found to follow a change in either the atmospheric or ocean model component between the analysis and forecast phases: changes in the ocean component can lead to sea surface temperature shocks of more than 0.5K in some equatorial regions during the first day of the forecast. Implications for the development of coupled forecast systems, particularly with respect to coupled data assimilation methods, are discussed.

Projected changes in tropical cyclones over Vietnam and the South China Sea using a 25 km regional climate model perturbed physics ensemble

The regional climate modelling system PRECIS, was run at 25 km horizontal resolution for 150 years (1949-2099) using global driving data from a five member perturbed physics ensemble (based on the coupled global climate model HadCM3). Output from these simulations was used to investigate projected changes in tropical cyclones (TCs) over Vietnam and the South China Sea due to global warming (under SRES scenario A1B). Thirty year climatological mean periods were used to look at projected changes in future (2069-2098) TCs compared to a 1961-1990 baseline. Present day results were compared qualitatively with IBTrACS observations and found to be reasonably realistic. Future projections show a 20-44 % decrease in TC frequency, although the spatial patterns of change differ between the ensemble members, and an increase of 27-53 % in the amount of TC associated precipitation. No statistically significant changes in TC intensity were found, however, the occurrence of more intense TCs (defined as those with a maximum 10 m wind speed > 35 m/s) was found to increase by 3-9 %. Projected increases in TC associated precipitation are likely caused by increased evaporation and availability of atmospheric water vapour, due to increased sea surface and atmospheric temperature. The mechanisms behind the projected changes in TC frequency are difficult to link explicitly; changes are most likely due to the combination of increased static stability, increased vertical wind shear and decreased upward motion, which suggest a decrease in the tropical overturning circulation.