B. D. Santer

Statistical significance of trends and trend differences in layer-average atmospheric temperature time series

This paper examines trend uncertainties in layer-average free atmosphere temperatures arising from the use of different trend estimation methods. It also considers statistical issues that arise in assessing the significance of individual trends and of trend differences between data sets. Possible causes of these trends are not addressed. We use data from satellite and radiosonde measurements and from two reanalysis projects. To facilitate intercomparison, we compute from reanalyses and radiosonde data temperatures equivalent to those from the satellite-based Microwave Sounding Unit (MSU). We compare linear trends based on minimization of absolute deviations (LA) and minimization of squared deviations (LS). Differences are generally less than 0.05°C/decade over 1959–1996. Over 1979–1993, they exceed 0.10°C/decade for lower tropospheric time series and 0.15°C/decade for the lower stratosphere. Trend fitting by the LA method can degrade the lower-tropospheric trend agreement of 0.03°C/decade (over 1979–1996) previously reported for the MSU and radiosonde data. In assessing trend significance we employ two methods to account for temporal autocorrelation effects. With our preferred method, virtually none of the individual 1979–1993 trends in deep-layer temperatures are significantly different from zero. To examine trend differences between data sets we compute 95% confidence intervals for individual trends and show that these overlap for almost all data sets considered. Confidence intervals for lower-tropospheric trends encompass both zero and the model-projected trends due to anthropogenic effects. We also test the significance of a trend in d(t), the time series of differences between a pair of data sets. Use of d(t) removes variability common to both time series and facilitates identification of small trend differences. This more discerning test reveals that roughly 30% of the data set comparisons have significant differences in lower-tropospheric trends, primarily related to differences in measurement system. Our study gives empirical estimates of statistical uncertainties in recent atmospheric temperature trends. These estimates and the simple significance testing framework used here facilitate the interpretation of previous temperature trend comparisons involving satellite, radiosonde, and reanalysis data sets.

Climate forcings in Goddard Institute for Space Studies SI2000 simulations

[1] We define the radiative forcings used in climate simulations with the SI2000 version of the Goddard Institute for Space Studies (GISS) global climate model. These include temporal variations of well-mixed greenhouse gases, stratospheric aerosols, solar irradiance, ozone, stratospheric water vapor, and tropospheric aerosols. Our illustrations focus on the period 1951–2050, but we make the full data sets available for those forcings for which we have earlier data. We illustrate the global response to these forcings for the SI2000 model with specified sea surface temperature and with a simple Q-flux ocean, thus helping to characterize the efficacy of each forcing. The model yields good agreement with observed global temperature change and heat storage in the ocean. This agreement does not yield an improved assessment of climate sensitivity or a confirmation of the net climate forcing because of possible compensations with opposite changes of these quantities. Nevertheless, the results imply that observed global temperature change during the past 50 years is primarily a response to radiative forcings. It is also inferred that the planet is now out of radiation balance by 0.5 to 1 W/m 2 and that additional global warming of about 0.5� C is already ‘‘in the pipeline.’’ INDEX TERMS: 1620 Global Change: Climate dynamics (3309); 1635 Global Change: Oceans (4203); 1650 Global Change: Solar variability;

Detection and Attribution of Streamflow Timing Changes to Climate Change in the Western United States

Abstract This article applies formal detection and attribution techniques to investigate the nature of observed shifts in the timing of streamflow in the western United States. Previous studies have shown that the snow hydrology of the western United States has changed in the second half of the twentieth century. Such changes manifest themselves in the form of more rain and less snow, in reductions in the snow water contents, and in earlier snowmelt and associated advances in streamflow “center” timing (the day in the “water-year” on average when half the water-year flow at a point has passed). However, with one exception over a more limited domain, no other study has attempted to formally attribute these changes to anthropogenic increases of greenhouse gases in the atmosphere. Using the observations together with a set of global climate model simulations and a hydrologic model (applied to three major hydrological regions of the western United States—the California region, the upper Colorado River basin, ...

Detecting and Attributing External Influences on the Climate System: A Review of Recent Advances

Abstract This paper reviews recent research that assesses evidence for the detection of anthropogenic and natural external influences on the climate. Externally driven climate change has been detected by a number of investigators in independent data covering many parts of the climate system, including surface temperature on global and large regional scales, ocean heat content, atmospheric circulation, and variables of the free atmosphere, such as atmospheric temperature and tropopause height. The influence of external forcing is also clearly discernible in reconstructions of hemispheric-scale temperature of the last millennium. These observed climate changes are very unlikely to be due only to natural internal climate variability, and they are consistent with the responses to anthropogenic and natural external forcing of the climate system that are simulated with climate models. The evidence indicates that natural drivers such as solar variability and volcanic activity are at most partially responsible fo...

Arctic Oscillation response to volcanic eruptions in the IPCC AR4 climate models

[1]xa0Stratospheric sulfate aerosol particles from strong volcanic eruptions produce significant transient cooling of the troposphere and warming of the lower stratosphere. The radiative impact of volcanic aerosols also produces a response that generally includes an anomalously positive phase of the Arctic Oscillation (AO) that is most pronounced in the boreal winter. The main atmospheric thermal and dynamical effects of eruptions typical of the past century persist for about two years after each eruption. In this paper we evaluate the volcanic responses in simulations produced by seven of the climate models included in the model intercomparison conducted as part of the preparation of the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). We consider global effects as well as the regional circulation effects in the extratropical Northern Hemisphere focusing on the AO responses forced by volcanic eruptions. Specifically we analyze results from the IPCC historical runs that simulate the evolution of the circulation over the last part of the 19th century and the entire 20th century using a realistic time series of atmospheric composition (greenhouse gases and aerosols). In particular, composite anomalies over the two boreal winters following each of the nine largest low-latitude eruptions during the period 1860–1999 are computed for various tropospheric and stratospheric fields. These are compared when possible with observational data. The seven IPCC models we analyzed use similar assumptions about the amount of volcanic aerosols formed in the lower stratosphere following the volcanic eruptions that have occurred since 1860. All models produce tropospheric cooling and stratospheric warming as in observations. However, they display a considerable range of dynamic responses to volcanic aerosols. Nevertheless, some general conclusions can be drawn. The IPCC models tend to simulate a positive phase of the Arctic Oscillation in response to volcanic forcing similar to that typically observed. However, the associated dynamic perturbations and winter surface warming over Northern Europe and Asia in the post-volcano winters is much weaker in the models than in observations. The AR4 models also underestimate the variability and long-term trend of the AO. This deficiency affects high-latitude model predictions and may have a similar origin. This analysis allows us to better evaluate volcanic impacts in up-to-date climate models and to better quantify the model Arctic Oscillation sensitivity to external forcing. This potentially could lead to improving model climate predictions in the extratropical latitudes of the Northern Hemisphere.

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 0.32°C to 0.67°C over the 20th century. The 22 climate models examined here suggest that century-timescale SST changes of this magnitude cannot be explained solely by unforced variability of the climate system. We employ model simulations of natural internal variability to make probabilistic estimates of the contribution of external forcing to observed SST changes. For the period 1906–2005, we find an 84% chance that external forcing explains at least 67% of observed SST increases in the two tropical cyclogenesis regions. Model “20th-century” simulations, with external forcing by combined anthropogenic and natural factors, are generally capable of replicating observed SST increases. In experiments in which forcing factors are varied individually rather than jointly, human-caused changes in greenhouse gases are the main driver of the 20th-century SST increases in both tropical cyclogenesis regions.

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. The “top 10” and “bottom 10” models are selected with three different sets of skill measures and two different ranking approaches. The entire D&A analysis is then repeated with each of these different sets of more or less skillful models. Our performance metrics include the ability to simulate the mean state, the annual cycle, and the variability associated with El Niño. We find that estimates of an anthropogenic water vapor fingerprint are insensitive to current model uncertainties, and are governed by basic physical processes that are well-represented in climate models. Because the fingerprint is both robust to current model uncertainties and dissimilar to the dominant noise patterns, our ability to identify an anthropogenic influence on observed multidecadal changes in water vapor is not affected by “screening” based on model quality.

Anthropogenic and Natural Influences in the Evolution of Lower Stratospheric Cooling

Observations reveal that the substantial cooling of the global lower stratosphere over 1979–2003 occurred in two pronounced steplike transitions. These arose in the aftermath of two major volcanic eruptions, with each cooling transition being followed by a period of relatively steady temperatures. Climate model simulations indicate that the space-time structure of the observed cooling is largely attributable to the combined effect of changes in both anthropogenic factors (ozone depletion and increases in well-mixed greenhouse gases) and natural factors (solar irradiance variation and volcanic aerosols). The anthropogenic factors drove the overall cooling during the period, and the natural ones modulated the evolution of the cooling.

Total volcanic stratospheric aerosol optical depths and implications for global climate change

Understanding the cooling effect of recent volcanoes is of particular interest in the context of the post-2000 slowing of the rate of global warming. Satellite observations of aerosol optical depth above 15u2009km have demonstrated that small-magnitude volcanic eruptions substantially perturb incoming solar radiation. Here we use lidar, Aerosol Robotic Network, and balloon-borne observations to provide evidence that currently available satellite databases neglect substantial amounts of volcanic aerosol between the tropopause and 15u2009km at middle to high latitudes and therefore underestimate total radiative forcing resulting from the recent eruptions. Incorporating these estimates into a simple climate model, we determine the global volcanic aerosol forcing since 2000 to be −0.19u2009±u20090.09u2009Wm−2. This translates into an estimated global cooling of 0.05 to 0.12°C. We conclude that recent volcanic events are responsible for more post-2000 cooling than is implied by satellite databases that neglect volcanic aerosol effects below 15u2009km.

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.