2.2. Regional moisture contributions from FLEXPART
We set the regional sources of atmospheric moisture (Fig. 2), based on
Hoyos et al. (2018), as follows: Tropical North Pacific (TNP), Tropical
South Pacific (TSP), Subtropical North Atlantic (STNA), Tropical North
Atlantic (TNA), Tropical Atlantic (TA), Tropical South Atlantic (TSA),
Caribbean Sea (CARS), Northern South America (NOSA), Orinoco Basin
(ORIC), Northern Amazon Basin (NAMZ), and Southern Amazon Basin (SAMZ).
In Hoyos et al. (2018), these zones were determined by the best
agreement among the Dynamical Recycling Model (DRM), the
Quasi-Isentropic Model (QIBT), and the Flexible Particle Dispersion
Model (FLEXPART).
[Insert Figure 2]
The FLEXPART is a 3D Lagrangian dispersion model that accounts for the
net loss (or gain) of specific humidity, q, along with a large
number of backward/forward trajectories between source and target areas
(Stohl & James, 2005, 2004; Gimeno et al., 2012; Sodeman et al., 2015).
The moisture contribution from a source area is estimated by accounting
for the vertically-integrated long-term balance of precipitation P and
evaporation E along the trajectories for a large number of computational
particles (2 million). Net E − P < 0 represents a loss of
moisture (precipitation exceeds evaporation), and E − P > 0
represents a gain of moisture (evaporation exceeds precipitation) (Stohl
& James, 2005, 2004). The diagnostic precipitation (P) corresponds to
the climatological sum of |E - P < 0| over
the entire period.
Here, we estimate the composition of moisture contributions using the
experiment developed by Hoyos et al., (2018). However, we calculate the
seasonal values considering the optimal transport day (that is, the day
when the moisture transference is maximum) instead of the 10-day global
mean lifetime of water vapor in the atmosphere (Numaguti, 1999; Gimeno,
Nieto, Drumond, Castillo, & Trigo, 2013; Van der Ent & Tuinenburg,
2017; Gimeno et al., 2021). This experimental design accounts for the
fact that the time scale at which the regional atmospheric moisture is
exchanged depends on the dynamic relationship between source and target
regions (including not only distance but also the intensity of the
advective processes and mechanisms that cause precipitation). We expect
that, as the integration time of the moisture trajectories increases,
the contribution of each source region correspondingly increases until
reaching the maximum contribution value, after which moisture
contribution shows a decreasing or asymptotic behavior (Hoyos et al.,
2017; Nieto & Gimeno, 2019). Setting integration times at the optimum
allows us to avoid over (or under) estimations in the relative
contributions of moisture sources. The period simulated 1980-2012,
includes the availability period of rainwater isotope records.