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.

Identification of human-induced changes in atmospheric moisture content.

Data from the satellite-based Special Sensor Microwave Imager (SSM/I) show that the total atmospheric moisture content over oceans has increased by 0.41 kg/m(2) per decade since 1988. Results from current climate models indicate that water vapor increases of this magnitude cannot be explained by climate noise alone. In a formal detection and attribution analysis using the pooled results from 22 different climate models, the simulated "fingerprint" pattern of anthropogenically caused changes in water vapor is identifiable with high statistical confidence in the SSM/I data. Experiments in which forcing factors are varied individually suggest that this fingerprint "match" is primarily due to human-caused increases in greenhouse gases and not to solar forcing or recovery from the eruption of Mount Pinatubo. Our findings provide preliminary evidence of an emerging anthropogenic signal in the moisture content of earth's atmosphere.

Detection of a direct carbon dioxide effect in continental river runoff records.

Continental runoff has increased through the twentieth century despite more intensive human water consumption. Possible reasons for the increase include: climate change and variability, deforestation, solar dimming, and direct atmospheric carbon dioxide (CO2) effects on plant transpiration. All of these mechanisms have the potential to affect precipitation and/or evaporation and thereby modify runoff. Here we use a mechanistic land-surface model and optimal fingerprinting statistical techniques to attribute observational runoff changes into contributions due to these factors. The model successfully captures the climate-driven inter-annual runoff variability, but twentieth-century climate alone is insufficient to explain the runoff trends. Instead we find that the trends are consistent with a suppression of plant transpiration due to CO2-induced stomatal closure. This result will affect projections of freshwater availability, and also represents the detection of a direct CO2 effect on the functioning of the terrestrial biosphere.

External control of 20th century temperature by natural and anthropogenic forcings.

A comparison of observations with simulations of a coupled ocean-atmosphere general circulation model shows that both natural and anthropogenic factors have contributed significantly to 20th century temperature changes. The model successfully simulates global mean and large-scale land temperature variations, indicating that the climate response on these scales is strongly influenced by external factors. More than 80% of observed multidecadal-scale global mean temperature variations and more than 60% of 10- to 50-year land temperature variations are due to changes in external forcings. Anthropogenic global warming under a standard emissions scenario is predicted to continue at a rate similar to that observed in recent decades.