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Assessing the performance of seasonal snow in the NARCCAP RCMs – An
analyses for the Upper Colorado River Basin
Nadine Salzmann (1,2,3) and Linda Mearns (3)
(1) University of Zurich, Department of Geography, Switzerland, nadine.salzmann@geo.uzh.ch
(2) University of Fribourg, Department of Geosciences, Switzerland
(3) National Center for Atmospheric Research, Institute for the Study of Society and Environment (NCAR/ISSE), Boulder,
CO, USA
1. Introduction
Seasonal snow is a major component of the hydrological
cycle and thus of the climate system Cohen and Rind (1991).
The dynamics of the snow cover depends on the atmospheric
circulation, which in turn is thermodynamically influenced
by the snow pack.
In mountain regions, the dynamics of the seasonal snow
cover is a key factor for hydrological run off and consequent
availability of water for human consumption, irrigation and
power generation e.g. Barnett et al. (2005). Due to the
proximity to the melting point, snow is particular sensitive
to changes in the atmospheric conditions with significant
effects on the timing and magnitude of hydrological run off.
Among the most promising tools for assessing future
changes in the hydrological run off in mountain regions is
Regional Climate Models (RCMs). They are able to simulate
and provide climate input variables on a regional scale and
for heterogeneous landscapes such as mountain topography
Leung and Qian (2003). However, so far only a few studies
analyzed the performance of mountain snow in RCMs.
There are many reasons for that, including foremost the
general difficulties associated with process-modeling in
complex topography and the lack of ample snow
observations in most mountain regions worldwide for
validation purposes.
Despite these limitations, here, we aim at assessing the
performance of the seasonal snow in the RCM simulations
calculated for the international RCM program NARCCAP
(North American Climate Change Program,
www.narccap.ucar.edu) Mearns et al. (2005).
2. Study site and data
The following analyses are conducted for the region of the
Upper Colorado River Basin (UCRB) in the U.S. Rocky
Mountains. Here, the seasonal snow pack of the highest
peaks contributes about 70 % of the Colorado River’s total
annual run off Christensen et al. (2004). Within the
perimeter of the UCRB, 45 SNOTEL observation stations
exist, most of them measuring Snow Water Equivalent
(SWE), 2m Temperature (2mT) and precipitation (Precip),
since 1981 and before. In addition to these point
measurements, a second source of ‘observation’ is used in
this study; the gridded NARR data (North American
Regional Re-analyses), with a horizontal resolution of 32
km. SNOTEL and NARR are compared in the following
with results from NARCCAP simulations. Only NCEPdriven
NARCCAP runs are used in a first step. The
comparison includes the following RCMs, listed with the
respective Landsurface Scheme (LSS) used in each RCM. It
is in the LSS, where the processes concerning the snow
dynamics are defined.
ECPC (Experimental Climate Prediction Center) from
Scripps Institution of Oceanography, La Jolla, CA, USA.
LSS: NOAH
MRCC (Modèle Régional Canadien du Climat) from
Ouranos Consortium, Montreal (Quebec), Canada.
LSS: CLASS
RegCM3 (REGional Climate Model) from UC Santa
Cruz, ITCP, USA.
LSS: BATS
WRF (Weather Research and Forecasting Model) from
Pacific Northwest National Lab, Washington, USA.
LSS: NOAH
MM5 (Mesoscale Meteorologic Model) from Iowa State
University, Iowa, USA.
LSS: NOAH
All RCMs are run with a grid spacing of 50 km and cover
the UCRB by 10 grid boxes.
3. Analyses and some results
‘SWE’ and the two related variables ‘2mT’ and ‘Precip’
were compared and analyzed in various spatial and
temporal terms.
It was found that NARCCAP RCMs generally simulate
higher air temperatures than NARR and particularly than
SNOTEL. However, the departures are relatively constant
within different elevation levels, indicating that
theoretically a lapse rate correction could be applied for
adjusting the NARCCAP results towards the SNOTEL
measurements. Though, based on the relatively small
elevation difference between the SNOTEL and
NARCCAP topography, the lapse-rate factor only explains
a minor part of the deviation.
Regarding precipitation the NARCCAP models are in
general too dry compared to SNOTEL.
A large-scale factor that influences the climate and
particularly precipitation on the Colorado Plateau is the
ENSO. Major El Niño events as e.g. in 1982-83, 1992-93
and 1994-95 produce during winter exceptionally wet
weather in the region. It is thus of interest, if these events
are reflected in the datasets. However, no clear evidence
is found in any of the datasets used here, pointing towards
ENSO events.
Finally, SWE, shows significant departures between the
different RCMs, and also compared to SNOTEL and
NARR. While the annual cycle is captured relatively well,
the amount of snow as well as the duration and the time of
maximum vertical snow depth are significantly
underestimated by the NARCCAP RCMs and NARR