Identification of human-induced changes in atmospheric moisture content

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   Fig. 1.

   Anomaly time series of monthly mean 〈W _o〉, the spatial average of total atmospheric moisture over near-global (50°N–50°S) oceans (A) and an estimate of the stratospheric aerosol optical depth (SAOD) (21) (B). Observations of 〈W _o〉 are from the SSM/I data set (20). Simulated 〈W _o〉 data are from 49 realizations of 20th century climate change that included combined anthropogenic and natural external forcing (ALL), performed with 12 different models. Model results were averaged over realizations and models (see footnote l). Both model and observational data were smoothed by using a filter with a half-power point at ≈2 years (see SI Text). The yellow and gray envelopes are the 1σ and 2σ confidence intervals (respectively) for the multimodel average, calculated at each time t with a sample size n = 12. Most of the 20CEN experiments end in December 1999, and the multimodel average is displayed until that month only. All model anomalies were defined relative to climatological monthly means over 1900–1909. The choice of reference period has no impact on subsequent trend analyses or variability estimates. SSM/I anomalies were forced to have the same mean as the ALL average over the period of overlap between the simulated and observed time series (1988–1999). Note that the amplitude of 〈W _o〉 variability is not directly comparable in the observations and ALL model average because the latter was damped by averaging over different realizations and models. Vertical lines denote the times of maximum SAOD after major volcanic eruptions.

   
   
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   Fig. 2.

   Comparison of observed 〈W _o〉 trends with model simulations of unforced (A) and externally forced (B) trends. The sampling distribution of unforced 19-year trends was calculated as described in the text. Residual control run drift was not subtracted before estimation of the trend sampling distribution, thus inflating the standard error of the distribution and making it more difficult to reject the null hypothesis that internal variability alone could explain the observed trend. Forced 〈W _o〉 trends over 1988–1999 were estimated from 71 realizations of the 20CEN experiment performed with 22 models (see SI Tables 2 and 3). The SSM/I trend over 1988–1999 is larger than the mean of the model distribution of forced trends, in part because of the effects of the large observed El Niño event in 1997/1998 (Fig. 1 A), which is close to the end of the trend period used in B.

   
   
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   Fig. 3.

   Comparison of basic statistical properties of simulated and observed means, variability, and trends for atmospheric moisture over near-global oceans. Scatterplots show the relationships between the temporal standard deviation of unfiltered 〈W _o〉 anomalies and climatological annual mean 〈W _o〉 (A), the temporal standard deviation of 2-year filtered 〈W _o〉 anomalies (see SI Text) and linear trends in 〈W _o〉 over 1988–1999 (B), and the standard deviation of SST anomalies in the Niño 3.4 region (12) and the temporal correlation between anomalies of 〈W _o〉 and 〈T _o〉 (where 〈T _o〉 is the spatially averaged SST anomaly over 50°N–50°S) (C). Model results are individual 20CEN realizations and are partitioned into ALL and ANTHRO models (circles and triangles, respectively). Observations are from SSM/I for 〈W _o〉 and from version 2 of the Extended Reconstructed SST (ERSST) data set of the National Oceanic and Atmospheric Administration (NOAA) for 〈T _o〉 (25). All calculations involve monthly mean, spatially averaged anomaly data for the period January 1988 through December 1999, with anomalies expressed relative to climatological monthly means over this period. Standard deviations and correlations were estimated from linearly detrended data. The dashed horizontal and vertical lines in A–C are at the locations of the SSM/I values (SSM/I and ERSST in C) and facilitate visual comparison of the modeled and observed results. The error bars on the observed 〈W _o〉 trend in B are the 2σ trend confidence intervals, adjusted for temporal autocorrelation effects (see SI Text).

   
   
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   Fig. 4.

   Simulated and observed spatial patterns of changes in W _o and estimation of detection time (10). Multimodel averages of the 20th century changes in W _o were used to calculate the ALL (A) and ANTHRO (B) fingerprints we search for in the observations. Also shown are the leading noise modes of the concatenated ALL (C) and ANTHRO (D) model control runs and the observed pattern of total linear changes in W _o over 1998–2006 (E). All calculations were performed on the common 10° × 10° latitude/longitude grid used for the fingerprint analysis. The method used for estimation of detection time (F) is illustrated for one specific example, in which W _o changes from both SSM/I data and the concatenated ANTHRO model control runs were projected onto the ANTHRO model fingerprint patterns. We fit trends of increasing length L to the resulting “signal” and “noise” projection time series, Z(t) and N(t), respectively; form a trend S/N as described in SI Text; and then determine the time at which this ratio exceeds and remains above a stipulated 5% significance threshold. This is the detection time. The dashed vertical lines denote the detection times for the raw and optimized fingerprints (1999 and 2002, respectively). In this example, data from the concatenated ALL model control runs were used for fingerprint optimization.

   
   
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   Fig. 5.

   Precipitable water changes in model single-forcing runs. Shown are column-integrated changes in monthly mean 〈W _o〉 in experiments performed with the Parallel Climate Model (PCM) (28) (A) and the MIROC3.2(medres) model (29) (B). For each model, there are a total of six experiments. In the first five, climate forcings were varied individually according to estimates of their historical changes over the 20th century. The five forcings considered were changes in well mixed GHGs, anthropogenic aerosol effects, tropospheric and stratospheric ozone, solar irradiance, and volcanic aerosols. These forcings were varied simultaneously in the sixth experiment (ALL). In PCM, the anthropogenic aerosol forcing involves only the direct (scattering) effects of sulfate aerosols. The MIROC anthropogenic aerosol experiment considers forcing by both the direct and indirect effects of sulfate and carbonaceous aerosols (29) (see SI Table 2). All changes in 〈W _o〉 were defined relative to climatological monthly means over 1900–1909. Results are ensemble averages and were decadally filtered (K = 145 months) to damp high-frequency noise (see SI Text). The ensemble size was 10 for the MIROC ALL integration and 4 for the PCM ALL experiment and for each PCM and MIROC single-forcing run (except the PCM volcanic forcing case, for which only two realizations were available).