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Use of regional climate models in regional attribution studies
Christopher J. Anderson 1 , William J. Gutowski 1 , Jr., Martin P. Hoerling 2 and Xiaowei Quan 2
1 3010 Agronomy Hall, Iowa State University, Ames, 50011-1010, cjames@iastate.edu
2 Earth Systems Research Laboratory, Physical Sciences Division, 325 Broadway, Boulder, CO, 80305-3328
1. Introduction
Attribution is the scientific process whether an identified
change is consistent with an expected response to a
combination of external forcing mechanisms and
inconsistent with alternative, plausible explanations for
which important elements are excluded from the
combination of forcing mechanisms. Currently, the IPCC
(IPCC, 2007) concludes:
“Difficulties remain in attributing temperature changes on
smaller than continental scales and over time scales of less
than 50 years. Attribution at these scales, with limited
exceptions, has not yet been established. Averaging over
smaller regions reduces the natural variability less than does
averaging over large regions, making it more difficult to
distinguish between changes expected from different
external forcings, or between external forcing and
variability.”
An alternative to reducing dimensionality by averaging is to
apply attribution techniques to a particular physical process
rather than over a summation of all processes. Two
examples are provided herein.
2. Attribution of Seasonal Extremes of Water
Vapor Flux Convergence
An increasing trend over the past century in frequency and
intensity of precipitation >4” has been found to be
statistically significant in the upper Midwest United States
(CCSP, 2008). Precipitation has large spatial variability,
especially high-rate precipitation, making attribution studies
susceptible to poor signal-to-noise ratio. Furthermore, it is
difficult to simulate these extreme precipitation rates
whether using global or regional climate models. However,
the representation of the linkages between atmospheric
processes and extreme precipitation in the Midwest United
States by regional climate models is superior to that of
analysis used to drive them (Anderson et al. 2003), and
provides the possibility of focusing attribution studies on the
processes that lead to extreme precipitation rather than
extreme precipitation itself.
The attribution problem is one in which a one-way
downscaling technique is appropriate for the following two
reasons. First, the convective processes and feedback into
the large-scale circulation is believed to be largely
constrained to the region of heavy rainfall and regions
nearby. Second, the convective processes require the ability
to simulate correctly the coupling of mesoscale circulations.
The attribution approach begins with downscaling two
global climate model simulations of the 20 th century: one
with increasing greenhouse gas concentrations and one with
constant pre-industrial values. What is important to analyze
is the components of the water vapor flux convergence,
which is comprised of the product of water vapor and
velocity convergence added to the advection of water vapor.
Because the atmospheric processes have a larger scale and
slower time evolution than storms that produce precipitation
>4”, it is less likely to be subject to the same signal-tonoise
ratio problem. Furthermore, the components of the
moisture flux convergence may be related to different
expected responses to climate change. In particular, the
velocity convergence will be related to the position of the
storm track and its volatility; whereas, the water vapor
advection will be related to the moisture content of the air
due to evaporation from the Gulf of Mexico sea surface
and evapotranspiration in nearby land regions. Thus, the
interpretation of how climate change affects conditions
conducive to >4” precipitation may be much cleaner than
the interpretation for >4” precipitation itself.
3. Attribution of a climate extreme
One-way downscaling with regional climate models may
also be used for attribution of an individual extreme event.
In this case, the forcing mechanisms of interest evolve on
a seasonal or sub-seasonal scale rather than over multiple
decades. Attribution of the 2008 Midwest flood is one
example.
The attribution methodology first seeks to determine
whether the precipitation that led to the 2008 Midwest
flood is consistent with the precipitation that is expected
given the slowly-varying global sea surface temperatures
or some particular pattern within the global sea surface
temperatures. The main tool used in this analysis would
be a global climate model with specified sea surface
temperature as a lower boundary condition (an external
forcing mechanism).
Another slowly varying factor to consider is the surface
wetness. The feedback of soil moisture into precipitation
is a process that is much easier to isolate than heavy
precipitation rates themselves. In this attribution
problem, an estimate of the soil moisture is provided as a
boundary condition and atmospheric analyses rather than
global climate model simulations are used as lateral
boundary conditions to a regional model. Thus, there are
two external forcing mechanisms: the large-scale
circulation and the soil moisture pattern. An ensemble is
used to assess the precipitation variability and is generated
by initializing on different dates but retaining the
estimated soil moisture pattern as a boundary condition. It
is necessary to define an alternative pattern to examine
whether other soil moisture patterns produce a similar
response. Candidates for alternative patterns might
include a soil moisture anomaly of opposite phase or a
climatological soil moisture pattern.
4. Summary
The role of regional climate models in attribution studies
is likely to expand as interest shifts to examination of
regional climate change. A different perspective on
attribution is described here. Rather than averaging fields
to reduce variability, it is proposed that regional
attribution studies focus on coherent regional mechanisms
that are better simulated in regional models than global
models.