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Table 1
Prescribed values of atmospheric forcing scaling parameter f ΒΌ DF atm = DF
Forcing
CO 2
Other WMGHG
O 3 trop.
O 3 strat.
SO 4 (all)
BB
BC
Solar
f
0.8
0.5
-0.3
0.0
0.0
-0.9
2.5
0.2
Well-Mixed Greenhouse Gases (WMGHG) includes CH 4 ,N 2 O and CFCs; SO 4 includes all sulfate aerosol
forcings (direct, indirect and volcanic). BB biomass burning aerosol, BC black carbon aerosol
purpose of this analysis is illustrative only, inaccuracies in the prescribed radiative forcings
and other model parameters are not considered a serious impediment.
To compute DP using our simple model, we combine ( 2 ) with ( 3 - 4 ) where f is pre-
scribed as in Table 1 and assuming that DT DT m . Thus, DF atm is computed from DF at
each 1 year time step (Fig. 1 b); forcing agents that do not interact with the atmosphere
(e.g., purely scattering SO 4 aerosol) are assumed not to influence the fast DP responses.
The model simulated DT is depicted in Fig. 1 c and compares favorably with observed
estimates from the HadCRUT4 observations (Morice et al. 2012 ). The fast and slow
(T-dependent) components of DP are computed from ( 2 ) using the model simulated DT and
DF atm in Fig. 1 d. Also shown are estimates neglecting the fast response from Black Carbon
aerosol (-BC) and prescribing the HadCRUT4 DT for the slow component (dotted lines).
The slow DP component rises with DT at the rate 2 W m -2 K -1 , as prescribed by the
parameter k, and is relatively insensitive to the inclusion of BC aerosol or error in simu-
lated DT (although the recent hiatus in global temperature rises since *2000 are not
captured). The fast component leads to reduced DP, which is enhanced by the inclusion of
BC (additional atmospheric absorption of radiative energy leading to atmospheric stabil-
ization and declining global DP). Overall, the total DP response shows little global trend,
consistent with recent observationally based estimates (Adler et al. 2008 ), although
responses to volcanic forcings can introduce apparent trends over decadal timescales.
Inaccuracies in the model parameters, including the scaling factors, k and f, will reduce the
realism of the simple model estimates. It is, therefore, instructive to progress from the
simple model on to the considerably more detailed depiction of global precipitation
changes simulated by coupled climate model simulations.
2.2 Transient Response in Global Precipitation in CMIP5 Models
The simulated transient climate response is illustrated in Fig. 2 which shows DP simulated
by fully coupled climate models (see details in Table 2 ) as part of the Coupled Model
Intercomparison Project-phase 5 (CMIP5; Taylor et al. 2011 ). Fig. 2 a shows increases in
DP over the twenty-first century, rising by around 3-11 % over the period 2000-2100.
The RCP8.5 (Representative Concentration Pathways) scenario (an emissions pathway
leading to a radiative forcing of 8.5 W m -2 by 2100) simulates a larger response than the
more mitigating RCP4.5 scenario (as illustrated by the thick ensemble mean lines)
although there is considerable inter-ensemble spread. This is partly explained by the larger
DT response simulated by RCP8.5 as illustrated in Fig. 2 b. A simple linear fit between DP
and DT produces a sensitivity of *1 %/K; this is smaller than implied by the scaling
parameter k in ( 2 ) since rising greenhouse gas concentrations are muting the overall DP
response to warming by heating the atmosphere.
For each scenario, there is also a large inter-model spread, since models with higher
climate sensitivities (and/or slower rates of ocean heat uptake) tend to warm more rapidly
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