Supplementary material
A. Method section
2.1 Identification of the main oceanic moisture source regions. The moisture source
regions used in this work are based on the maxima of the annual climatological
vertically integrated moisture flux divergence (that is, E‐P) [Stohl and James, 2004] for
the 44‐year period between January 1980 and December 2000, using the available
ECMWF re‐analysis ERA-40, [Uppala et al.,, 2005] data on a 1° × 1° grid. The
vertically integrated moisture transport
the acceleration due to gravity,
is defined as:
is the specific humidity,
where
is
is the surface pressure, and
is the horizontal wind vector. Ten oceanic moisture source regions were identified
using a threshold of 750 mm/yr for the integrated moisture flux divergence [Gimeno et
al., 2010], (Figure 1, top). These regions were: the Coral Sea (referred to as CORALS);
the North and South Pacific (NPAC and SPAC, respectively); the Mexico Caribbean
Gulf (MEXCAR); the North and South Atlantic (NATL and SATL, respectively); the
Arabian Sea (ARAB); the Zanzibar Current (ZAN); the Agulhas Current (AGU); and
the Indian Ocean (IND). Two additional source regions were defined using their
physical boundaries: these were the Mediterranean Sea (MED) and the Red Sea
(REDS).
2.2 FLEXPART model. The FLEXPART model is a three dimensional Lagrangian
particle dispersion model. While the initial use of this model was to study of pollution
dispersion, it has become the standard tool for analyzing the trajectories and changing
properties of air parcels in atmospheric studies [Stohl and James, 2004, Stohl et al.,
2005]. In general terms, the FLEXPART model is accurate when simulating a range of
processes, including: long-range and mesoscale transport; diffusion and radioactive
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decay of tracers released from a source; and dry and wet deposition. Wind fluctuations
and convection are parameterized using schemes described in previous literature
[Hanna., 1982; Emanuel and Živković-Rothman., 1999] . To ensure mass balance,
spherical harmonic data are used to calculate the vertical winds. Details of the way of
including turbulence, the parameterization schemes of the planetary boundary layer and
mesoscale velocity fluctuations can be found in the FLEXPART technical note [Stohl et
al., 2005].
The FLEXPART model can be run either forwards or backwards in time. For forward
tracking, particles are “released” from a source and concentrations are determined
downwind on a grid; for backward tracking the particles are “released” from a receptor
area. The model allows the analysis of moisture transport between source and sink
areas, by dividing the atmosphere homogeneously into a large number of air parcels
(particles), which are transported using the three-dimensional wind field. The
FLEXPART model is supported by a large number of peer-reviewed publications, and
is well validated and of proven robustness.
2.3 Moisture budget. The net rate of change of water vapour of an air particle or air
parcel along a trajectory can be expressed as: e – p = m dq/dt, where (e-p) is the
increase or decrease in moisture along the trajectory according to the changes in (q)
with time (t) for an air parcel of mass m. The surface freshwater flux (E – P) can be
obtained by summing (e – p) for all the particles in the vertical atmospheric column
over an area, where E is the evaporation rate per unit area, and P is the precipitation rate
per unit area. In this work, the FLEXPART model was used to investigate the processes
involved in transporting moisture from the main oceanic sources regions around the
world for a 21-year period, from 1980 to 2000. The model was initialized in forward
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mode to track atmospheric moisture for the entire atmosphere using the ERA-40 reanalysis data set, [Uppala et al.,, 2005] , with 1º horizontal resolution, and vertical
resolution in 61 vertical levels. The atmosphere is divided homogenously into 1.9
million particles which are advected using the 3-D wind input data. Records were made
at 6 hour intervals (00, 06, 12 and 18 UTC) of the position and specific humidity values
(q) of every particle along its trajectory over a ten day period, which is the average time
that water vapour resides in the atmosphere [Numaguti, 1999]. A database was
constructed that identified all trajectories originating from oceanic moisture sources.
The (E-P) values, integrated over the ten days of transport, indicate the most important
sinks of moisture for each source, and also when the moisture was lost.
2.4 Composites considering the intensity of the sources of moisture. We define the
term “moisture source intensity” as the spatial average of the seasonal divergence of
vertically integrated moisture flux. When looking for possible impacts in the moisture
transport caused by changes in the intensity of a given source, the composite differences
between the average of the five highest intensity episodes and the average of the five
lowest intensity events identified for that source (High - Low) were obtained for JJA
and DJF. Changes in the moisture transport were analyzed through composites of E-P
fields associated with particle trajectories from the different oceanic moisture sources
generated by the FLEXPART model.
2.5 The bootstrap method of testing statistical significance. The test of the statistical
significance of composite differences was based on the methodology proposed by Wei
et al. [2012] , which applies the bootstrap test by permuting the original time series
[Efron and Tibshirani., 1983]. With small samples, the non-parametric bootstrap
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method may be adequate to evaluate the statistical significance. Taking the analysis of
changes in moisture source intensity as an example, we tested the significance of the
difference between the five highest and five lowest intensity events at a 90% confidence
level. Considering the 21 years of data (1980-2000), we selected two five-year periods
at random (total of 10 years) from these 21 years, and calculated their difference 1,000
times (this is a reasonable number of repetitions, according to Efron and Tibshirani,
[1983]. To be considered significant, the absolute value of the composite of differences
must be larger than 90% of the 1,000 differences.
2.6 Identification of oceanic regions with higher evaporation rate in a future
climate change scenario. Based on data generated by 15 of the GCM models included
in the Coupled Model Intercomparison Project phase 3 [Meehl, et al., 2007] and were
used for IPCC AR4, performed moisture budget calculations for a future period of
climate change between 2046 and 2065, and computed a multimodel ensemble mean
[Seager et al., 2010]. From the 24 models available within AR4 we have restricted our
analysis to 15 because calculation of changes in the modelled moisture budget requires
daily data for humidity and winds at a fine vertical resolution, which are only available
for these 15 models. The criteria for using only 15 of the 24 models and the list of them
can be found in the work by Seager et al. (2010) (see Table 1 in that paper). One of the
analyzed variables was the rate of change of (E-P). To identify regions of higher
changes, a comparison was made against the period 1961-2000 for the semiannual
periods of October-March and April-September. The 1961-2000 simulations were
forced with historical trace gas, aerosol, solar, volcanic and (in some cases) land use
change data, albeit with differences between models in how these forcings were treated.
The 2046-65 simulations used the “middle of the road” emissions scenario as identified
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by the Special Report on Emission Scenarios A1B (SRESA1B). Using the Seager
multimodel ensemble mean change data, we selected those oceanic areas where climate
changes led to an increase in evaporation (E) minus precipitation (P). The oceanic
moisture source regions were defined based on the threshold of 0.3 mm/yr. Twelve
areas were selected for the April-September period, and nine for October-March. These
regions were used with the FLEXPART model in forward mode to identify which
continental regions would be affected by changes in precipitation (E-P<0) originating in
each oceanic moisture source.
References
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B. Supplementary figures
Figure legends (supplementary material)
Figure S1: Values of (E‐P) integrated over 10 days for the period 1980-2000,
calculated by forward tracking from the oceanic regions excepting the moisture sources
indicated in the Figure 1. Only negative values less than -0.01 mm/day are plotted (E-P
< -0.01 mm/day). The left and right columns are for the periods DJF and JJA,
respectively.
Figure S2: Values of (E‐P) integrated over 10 days for the period 1980-2000,
calculated by forward tracking from the oceanic moisture sources indicated by the
closed pink lines and identified by their acronym. Only negative values less than -0.01
mm/day are plotted (E-P < -0.01 mm/day). The left and right columns are for the
periods DJF and JJA, respectively.
Figure S3. The composite differences in (E - P) between the average of the five highest
source intensity periods and the average of the five lowest intensity periods during
December-February (left panels) and June–August (right panels). Each moisture source
is shown on a separate pair of panels. The black contour lines indicate areas where
absolute values of the differences greater than 0.01 mm/day are significant at the 90%
confidence level, according to a bootstrap test that permutes the original time series
1,000 times
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Figure S1
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Figure S2
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Figure S3
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