Identifying island safe havens to prevent the extinction of the World's largest lizard from global warming.

The Komodo dragon () is an endangered, island-endemic species with a naturally restricted distribution. Despite this, no previous studies have attempted to predict the effects of climate change on this iconic species. We used extensive Komodo dragon monitoring data, climate, and sea-level change projections to build spatially explicit demographic models for the Komodo dragon.

StableClim, continuous projections of climate stability from 21000 BP to 2100 CE at multiple spatial scales.

Paleoclimatic data are used in eco-evolutionary models to improve knowledge of biogeographical processes that drive patterns of biodiversity through time, opening windows into past climate-biodiversity dynamics. Applying these models to harmonised simulations of past and future climatic change can strengthen forecasts of biodiversity change. StableClim provides continuous estimates of climate stability from 21,000 years ago to 2100 C.

Cradles of diversity are unlikely relics of regional climate stability.

The stability of regional climates on millennial timescales is theorised to be a primary determinant of nearby diversification [1-5]. Using simulated patterns of past temperature change at monthly timescales [6], we show that the locations of climatically stable regions are likely to have varied considerably across and within millennia during glacial-interglacial cycles of the Late Quaternary. This result has important implications for the role of regional climate stability in theories of speciation, because long-term climate refugia are typically presumed to be 'cradles' of diversity (areas of high speciation) only if they remain stable across Milankovitch climate oscillations [1-5], which operate on multi-millennial time scales [7].

Why decadal to century timescale palaeoclimate data are needed to explain present-day patterns of biological diversity and change.

The current distribution of species, environmental conditions and their interactions represent only one snapshot of a planet that is continuously changing, in part due to human influences. To distinguish human impacts from natural factors, the magnitude and pace of climate shifts, since the Last Glacial Maximum, are often used to determine whether patterns of diversity today are artefacts of past climate change. In the absence of high-temporal resolution palaeoclimate reconstructions, this is generally done by assuming that past climate change occurred at a linear pace between widely spaced (usually, ≥1,000 years) climate snapshots.

Human and natural influences on the changing thermal structure of the atmosphere.

Since the late 1970s, satellite-based instruments have monitored global changes in atmospheric temperature. These measurements reveal multidecadal tropospheric warming and stratospheric cooling, punctuated by short-term volcanic signals of reverse sign. Similar long- and short-term temperature signals occur in model simulations driven by human-caused changes in atmospheric composition and natural variations in volcanic aerosols.

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 fingerprint) and the noise of internally generated variability.

The reproducibility of observational estimates of surface and atmospheric temperature change.

Although concerns have been expressed about the reliability of surface temperature data sets, findings of pronounced surface warming over the past 60 years have been independently reproduced by multiple groups. In contrast, an initial finding that the lower troposphere cooled since 1979 could not be reproduced. Attempts to confirm this apparent cooling trend led to the discovery of errors in the initial analyses of satellite-based tropospheric temperature measurements.

Incorporating model quality information in climate change detection and attribution studies.

In a recent multimodel detection and attribution (D&A) study using the pooled results from 22 different climate models, the simulated "fingerprint" pattern of anthropogenically caused changes in water vapor was identifiable with high statistical confidence in satellite data. Each model received equal weight in the D&A analysis, despite large differences in the skill with which they simulate key aspects of observed climate. Here, we examine whether water vapor D&A results are sensitive to model quality.

Temperature increase of 21st century mitigation scenarios.

Estimates of 21st Century global-mean surface temperature increase have generally been based on scenarios that do not include climate policies. Newly developed multigas mitigation scenarios, based on a wide range of modeling approaches and socioeconomic assumptions, now allow the assessment of possible impacts of climate policies on projected warming ranges. This article assesses the atmospheric CO(2) concentrations, radiative forcing, and temperature increase for these new scenarios using two reduced-complexity climate models.

CLIMATE: A New Route Toward Limiting Climate Change?

Climate change mitigation strategies have focused on reductions in carbon dioxide and other long-lived greenhouse gases. Smith et al., investigate the viability of a different strategy, recently proposed by Hansen et al.

Simulated and observed variability in ocean temperature and heat content.

Observations show both a pronounced increase in ocean heat content (OHC) over the second half of the 20th century and substantial OHC variability on interannual-to-decadal time scales. Although climate models are able to simulate overall changes in OHC, they are generally thought to underestimate the amplitude of OHC variability. Using simulations of 20th century climate performed with 13 numerical models, we demonstrate that the apparent discrepancy between modeled and observed variability is largely explained by accounting for changes in observational coverage and instrumentation and by including the effects of volcanic eruptions.

A combined mitigation/geoengineering approach to climate stabilization.

Projected anthropogenic warming and increases in CO2 concentration present a twofold threat, both from climate changes and from CO2 directly through increasing the acidity of the oceans. Future climate change may be reduced through mitigation (reductions in greenhouse gas emissions) or through geoengineering. Most geoengineering approaches, however, do not address the problem of increasing ocean acidity.

Variations in solar luminosity and their effect on the Earth's climate.

Variations in the Sun's total energy output (luminosity) are caused by changing dark (sunspot) and bright structures on the solar disk during the 11-year sunspot cycle. The variations measured from spacecraft since 1978 are too small to have contributed appreciably to accelerated global warming over the past 30 years. In this Review, we show that detailed analysis of these small output variations has greatly advanced our understanding of solar luminosity change, and this new understanding indicates that brightening of the Sun is unlikely to have had a significant influence on global warming since the seventeenth century.

Forced and unforced ocean temperature changes in Atlantic and Pacific tropical cyclogenesis regions.

Previous research has identified links between changes in sea surface temperature (SST) and hurricane intensity. We use climate models to study the possible causes of SST changes in Atlantic and Pacific tropical cyclogenesis regions. The observed SST increases in these regions range from 0.

Volcanoes and climate: Krakatoa's signature persists in the ocean.

We have analysed a suite of 12 state-of-the-art climate models and show that ocean warming and sea-level rise in the twentieth century were substantially reduced by the colossal eruption in 1883 of the volcano Krakatoa in the Sunda strait, Indonesia. Volcanically induced cooling of the ocean surface penetrated into deeper layers, where it persisted for decades after the event. This remarkable effect on oceanic thermal structure is longer lasting than has previously been suspected and is sufficient to offset a large fraction of ocean warming and sea-level rise caused by anthropogenic influences.

Amplification of surface temperature trends and variability in the tropical atmosphere.

The month-to-month variability of tropical temperatures is larger in the troposphere than at Earth's surface. This amplification behavior is similar in a range of observations and climate model simulations and is consistent with basic theory. On multidecadal time scales, tropospheric amplification of surface warming is a robust feature of model simulations, but it occurs in only one observational data set.

The climate change commitment.

Even if atmospheric composition were fixed today, global-mean temperature and sea level rise would continue due to oceanic thermal inertia. These constant-composition (CC) commitments and their uncertainties are quantified. Constant-emissions (CE) commitments are also considered.

Contributions of anthropogenic and natural forcing to recent tropopause height changes.

Observations indicate that the height of the tropopause-the boundary between the stratosphere and troposphere-has increased by several hundred meters since 1979. Comparable increases are evident in climate model experiments. The latter show that human-induced changes in ozone and well-mixed greenhouse gases account for approximately 80% of the simulated rise in tropopause height over 1979-1999.

Influence of satellite data uncertainties on the detection of externally forced climate change.

Two independent analyses of the same satellite-based radiative emissions data yield tropospheric temperature trends that differ by 0.1 degrees C per decade over 1979 to 2001. The troposphere warms appreciably in one satellite data set, while the other data set shows little overall change.

Advanced technology paths to global climate stability: energy for a greenhouse planet.

Stabilizing the carbon dioxide-induced component of climate change is an energy problem. Establishment of a course toward such stabilization will require the development within the coming decades of primary energy sources that do not emit carbon dioxide to the atmosphere, in addition to efforts to reduce end-use energy demand. Mid-century primary power requirements that are free of carbon dioxide emissions could be several times what we now derive from fossil fuels (approximately 10(13) watts), even with improvements in energy efficiency.

Interpretation of high projections for global-mean warming.

The Intergovernmental Panel on Climate Change (IPCC) has recently released its Third Assessment Report (TAR), in which new projections are given for global-mean warming in the absence of policies to limit climate change. The full warming range over 1990 to 2100, 1.4 degrees to 5.

Interpreting differential temperature trends at the surface and in the lower troposphere.

Estimated global-scale temperature trends at Earth's surface (as recorded by thermometers) and in the lower troposphere (as monitored by satellites) diverge by up to 0.14 degrees C per decade over the period 1979 to 1998. Accounting for differences in the spatial coverage of satellite and surface measurements reduces this differential, but still leaves a statistically significant residual of roughly 0.

Anthropogenic influence on the autocorrelation structure of hemispheric-mean temperatures.

It is shown that lagged correlations for and cross-correlations between observed hemispheric-mean temperature data differ markedly from those for unforced (control-run) climate model simulations. The differences can be explained adequately by assuming that the observed data contain a significant externally forced component involving both natural (solar) and anthropogenic influences and that the global climate sensitivity is in the commonly accepted range. Solar forcing alone cannot reconcile the differences in autocorrelation structure between observations and model control-run data.